go-sound | Functional sound libraries for go | Audio Utils library

by padster Go Version: Current License: GPL-3.0

kandi X-RAY | go-sound Summary

go-sound is a Go library typically used in Audio, Audio Utils applications. go-sound has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Functional sound libraries for go

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kandi-support Support

go-sound has a low active ecosystem.
It has 94 star(s) with 14 fork(s). There are 7 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of go-sound is current.

go-sound Support

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go-sound Support

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quality kandi Quality

go-sound has no bugs reported.

go-sound Quality

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go-sound Quality

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security Security

go-sound has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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license License

go-sound is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

go-sound License

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build Reuse

go-sound releases are not available. You will need to build from source code and install.

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Top functions reviewed by kandi - BETA

kandi has reviewed go-sound and discovered the below as its top functions. This is intended to give you an instant insight into go-sound implemented functionality, and help decide if they suit your requirements.

NewResampler creates a new Resampler using the specified sourceRate and targetRate

NewCQKernel returns a new CQKernel .

NewConstantQ creates a ConstantQ .

NewCQInverse creates a new CQInverse .

Start the midi input .

playClairDeLune plays a chordDeLune

Play all the samples in a Sound .

Basic example for OpenGL .

makeWindow creates a window based on the window size .

ParseChord parses a chord string .

Get all kandi verified functions for this library.

go-sound Key Features

Functional sound libraries for go

go-sound Examples and Code Snippets

Community Discussions

Trending Discussions on Audio

How to get a smaller piece of audio from larger audio captured with browser's Web Audio Api
Audio widget within Jupyter notebook is **not** playing. How can I get the widget to play the audio?
FIXED Trying to Pause/Play MP3 file in HTML
Download audio file from html with javascript function
Result from audio FFT function makes it near impossible to inspect low/mid frequencies
Play multiple tracks <audio>
A problem with sound producing: How to make sound with Fourier coefficients
Get Latency of Bluetooth Headphoners UWP C++
Loading Wave File but there is random nonsense at the end of the data rather than the expected samples
How do i get the audio frequency from my mic using javascript?

Trending Discussions on Audio

QUESTION

How to get a smaller piece of audio from larger audio captured with browser's Web Audio Api

Asked 2022-Mar-22 at 12:33

I'm making a speech-to-text tool. I'm capturing audio in real time (using Web audio api from Chrome) and sending it to a server to convert the audio to text.

I'd like to extract pieces of the whole audio cause I only want to send sentences, avoiding silences. (cause the api I use has a cost). The problem is that I don't know how to convert the whole audio into pieces.

I was using MediaRecorder to capture the audio

    // recording 

    this.recorder = new MediaRecorder(stream)
    this.recorder.ondataavailable = async (e) => {
      const buffer = await e.data.arrayBuffer()
      this.chunks.add(new Uint8Array(buffer))
    }
    this.recorder.start(1000)

Now I have in this.chunks I have an array of buffers indexed by second.
If I try to reproduce the whole audio file by passing all captured buffer, it is able to decode it and reproduce it correctly:

    // reproduce the whole audio: <- this works
    const combinedChunks = this.chunks.reduce((prev, chunk) => [...prev,...chunk], [])
    const arrChunks = new Uint8Array(combinedChunks)
    this.repAudioContext = new AudioContext()
    this.repAudioBuffer = await this.repAudioContext.decodeAudioData(
      arrChunks.buffer
    )

    this.repSourceNode = this.repAudioContext.createBufferSource()
    this.repSourceNode.buffer = this.repAudioBuffer

    this.repSourceNode.connect(this.repAudioContext.destination)
    this.repSourceNode.start()

That works ^, because I'm using all of the pieces. But since I want to extract pieces of the audio, I want to be able to select only the buffer pieces I want to reproduce. And I can't do that. If I extract the first piece of audio, it stops working and I get: decodeAudioData - Unable to decode audio data.

    // reproduce a part of the audio captured: <- this won't work
    const combinedChunks = this.chunks.slice(1).reduce((prev, chunk) => [...prev,...chunk], []) // <- skipping first chunk
    const arrChunks = new Uint8Array(combinedChunks)
    this.repAudioContext = new AudioContext()
    this.repAudioBuffer = await this.repAudioContext.decodeAudioData(
      arrChunks.buffer
    )

    this.repSourceNode = this.repAudioContext.createBufferSource()
    this.repSourceNode.buffer = this.repAudioBuffer

    this.repSourceNode.connect(this.repAudioContext.destination)
    this.repSourceNode.start()

I understand this might be because in the first chunk there are headers or other metadata of the captured audio. But can't find a way of doing this.

Can anyone give me some advice? is there a different api I should be using? What's the proper way of extracting a smaller piece of audio from a larger one that I can reproduce and save as a file?

ANSWER

Answered 2022-Mar-22 at 12:33

I've found the answer to my own question, I was using the wrong approach.

What I need to use to get the raw audio inputs and be able to manipulate them is the AudioWorkletProcessor.

This video helped me to understand the theory behind:

https://www.youtube.com/watch?v=g1L4O1smMC0

And this article helped me understand how to make use of it: https://developer.mozilla.org/en-US/docs/Web/API/Web_Audio_API/Using_AudioWorklet

Source https://stackoverflow.com/questions/71470785

QUESTION

Audio widget within Jupyter notebook is **not** playing. How can I get the widget to play the audio?

Asked 2022-Mar-15 at 00:07

I writing my code within a Jupyter notebook in VS Code. I am hoping to play some of the audio within my data set. However, when I execute the cell, the console reports no errors, produces the widget, but the widget displays 0:00 / 0:00 (see below), indicating there is no sound to play.

Below, I have listed two ways to reproduce the error.

I have acquired data from the hub data store. Looking specifically at the spoken MNIST data set, I cannot get the data from the audio tensor to play

import hub
from IPython.display import display, Audio
from ipywidgets import interactive

# Obtain the data using the hub module
ds = hub.load("hub://activeloop/spoken_mnist")

# Create widget
sample = ds.audio[0].numpy()
display(Audio(data=sample, rate = 8000, autoplay=True))

The second example is a test (copied from another post) that I ran to see if it was something wrong with the data or something wrong with my console, environment, etc.

# Same imports as shown above

# Toy Function to play beats in notebook
def beat_freq(f1=220.0, f2=224.0):
    max_time = 5
    rate = 8000
    times = np.linspace(0,max_time,rate*max_time)
    signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)
    display(Audio(data=signal, rate=rate))
    return signal

v = interactive(beat_freq, f1=(200.0,300.0), f2=(200.0,300.0))
display(v)

I believe that if it is something wrong with the data (this is a well-known data set so, I doubt it), then only the second one will play. If it is something to do with the IDE or something else, then neither will work, as is the case now.

ANSWER

Answered 2022-Mar-15 at 00:07

Apologies for the late reply! In the future, please tag the questions with activeloop so it's easier to sort through (or hit us up directly in community slack -> slack.activeloop.ai).

Regarding the Free Spoken Digit Dataset, I managed to track the error with your usage of activeloop hub and audio display.

adding [:,0] to 9th line will help fixing display on Colab as Audio expects one-dimensional data

%matplotlib inline
import hub
from IPython.display import display, Audio
from ipywidgets import interactive

# Obtain the data using the hub module
ds = hub.load("hub://activeloop/spoken_mnist")

# Create widget
sample = ds.audio[0].numpy()[:,0]
display(Audio(data=sample, rate = 8000, autoplay=True))

(When we uploaded the dataset, we decided to upload the audio as (N,C) where C is the number of channels, which happens to be 1 for the particular dataset. The added dimension wasn't added automatically)

Regarding the VScode... the audio, unfortunately, would still not work (not because of us, but VScode), but you can still try visualizing Free Spoken Digit Dataset (you can play the music there, too). Hopefully this addresses your needs!

Let us know if you have further questions.

Mikayel from Activeloop

Source https://stackoverflow.com/questions/71200390

QUESTION

Play multiple tracks <audio>

Asked 2022-Feb-08 at 18:30

I'm trying to use the <audio> tag, and I want to have as many tracks playing as I add. But in the end, the very first track plays in a circle. How can this be fixed?

<audio id="audio" preload="" autoplay="" loop="">
  <source type="audio/mp3" src="music/mus1.mp3">
  <source type="audio/mp3" src="music/mus.mp3">
</audio>

<script type="text/javascript">
var audio = document.getElementById("audio");

function pVid() {
    audio.paused ? audio.play() : audio.pause();
}
</script>

ANSWER

Answered 2022-Feb-08 at 12:49

Add a skip button
when clicked, call a skip function that will
- pause if there is something playing then
- clear the playing/paused class clist
- increment the current to the next track
- then play

let sounds = new Array(new Audio("https://freesound.org/data/previews/46/46992_514283-lq.mp3"),
  new Audio("https://freesound.org/data/previews/610/610823_13156161-lq.mp3"),
  new Audio("https://freesound.org/data/previews/92/92005_1499847-lq.mp3"), new Audio("https://freesound.org/data/previews/46/46992_514283-lq.mp3"),
  new Audio("https://freesound.org/data/previews/610/610823_13156161-lq.mp3"),
  new Audio("https://freesound.org/data/previews/92/92005_1499847-lq.mp3"));

let current = random(0);
let paused = true;

// set event handlers on all audio objects
for (let s of sounds) {
  s.addEventListener('ended', ended);
  s.addEventListener('play', play);
  s.addEventListener('pause', pause);
}

updateVolume()

// handle button click
function playPause() {
  if (paused) {
    sounds[current].play();
    btn.innerText = 'pause';
    paused = false;

  } else {
    sounds[current].pause();
    btn.innerText = 'play';
    paused = true;
  }
}

// handle button skip
function skip() {
  if(!paused) playPause();
  document.getElementById(current + '').classList.remove('playing');
  document.getElementById(current + '').classList.remove('paused');
  current = (current + 1) % sounds.length;
  playPause();
}

function ended(e) {
  document.getElementById(current + '').classList.remove('playing');
  document.getElementById(current + '').classList.remove('paused');
  /*i++;
  if (i >= sounds.length) //loop
    i = 0;
  */
  current = random(current); // shuffle

  paused = true;
  playPause();
}

function play() {
  document.getElementById(current + '').classList.add('playing');
  document.getElementById(current + '').classList.remove('paused');
}

function pause() {
  document.getElementById(current + '').classList.add('paused');
  document.getElementById(current + '').classList.remove('playing');
}

function random(i) {
  let next = i;
  while (next == i)
    next = Math.floor(Math.random() * sounds.length);
  return next;
}

function updateVolume() {
  for (let s of sounds) {
    s.volume = volume.value;
  }
}

#list {
  margin-top: 1rem;
  border: 1px solid gray;
  width: 100px;
}

#controls {
  position: fixed;
  right: 2rem;
  top: 1rem;
  width: 50px;
}

#volume {
  width: 150px;
  height: 20px;
  transform-origin: 75px 75px;
  transform: rotate(-90deg) translateY(50%);
}

.playing {
  background-color: lightblue;
}

.paused {
  background-color: wheat;
}

<Button id=btn onClick='playPause()'>play</Button>
<Button id=btnSkip onClick='skip()'>skip</Button>
<div id=list>
  <div id='0'>Guitar</div>
  <div id='1'>Drum</div>
  <div id='2'>Violin</div>
  <div id='3'>Guitar</div>
  <div id='4'>Drum</div>
  <div id='5'>Violin</div>
</div>
<div id=controls>
  <label for="volume">Volume</label><br>
  <input id=volume type="range" id="volume" name="volume" min="0" max="1" step='.1' value='.5' onInput='updateVolume()'>

</div>

Source https://stackoverflow.com/questions/70957447

QUESTION

A problem with sound producing: How to make sound with Fourier coefficients

Asked 2022-Feb-04 at 23:39

I'm trying to create a sound using Fourier coefficients.

First of all please let me show how I got Fourier coefficients.

(1) I took a snapshot of a waveform from a microphone sound.

Getting microphone: getUserMedia()
Getting microphone sound: MediaStreamAudioSourceNode
Getting waveform data: AnalyserNode.getByteTimeDomainData()

The data looks like the below: (I stringified Uint8Array, which is the return value of getByteTimeDomainData(), and added length property in order to change this object to Array later)

const raw = '{"length": 512,"0":126,"1":121,"2":121,"3":124,"4":129,"5":135,"6":140,"7":147,"8":153,"9":156,"10":152,"11":141,"12":125,"13":112,"14":106,"15":108,"16":113,"17":120,"18":127,"19":132,"20":138,"21":142,"22":141,"23":136,"24":126,"25":115,"26":106,"27":103,"28":105,"29":111,"30":117,"31":121,"32":123,"33":124,"34":124,"35":120,"36":112,"37":103,"38":97,"39":95,"40":96,"41":98,"42":101,"43":106,"44":112,"45":117,"46":117,"47":113,"48":105,"49":98,"50":93,"51":91,"52":91,"53":92,"54":93,"55":95,"56":97,"57":101,"58":105,"59":108,"60":106,"61":101,"62":96,"63":95,"64":97,"65":100,"66":100,"67":97,"68":94,"69":94,"70":99,"71":104,"72":106,"73":105,"74":104,"75":105,"76":108,"77":111,"78":112,"79":110,"80":108,"81":105,"82":105,"83":107,"84":110,"85":113,"86":114,"87":115,"88":116,"89":120,"90":123,"91":125,"92":124,"93":121,"94":120,"95":121,"96":123,"97":124,"98":124,"99":126,"100":128,"101":131,"102":133,"103":134,"104":134,"105":134,"106":134,"107":134,"108":134,"109":133,"110":132,"111":131,"112":131,"113":134,"114":137,"115":139,"116":141,"117":142,"118":143,"119":142,"120":142,"121":139,"122":136,"123":131,"124":128,"125":128,"126":131,"127":134,"128":137,"129":139,"130":140,"131":141,"132":142,"133":141,"134":137,"135":132,"136":126,"137":122,"138":123,"139":127,"140":132,"141":135,"142":135,"143":134,"144":134,"145":135,"146":134,"147":130,"148":125,"149":121,"150":120,"151":121,"152":124,"153":129,"154":132,"155":134,"156":134,"157":133,"158":131,"159":129,"160":128,"161":127,"162":125,"163":124,"164":123,"165":124,"166":125,"167":128,"168":130,"169":131,"170":132,"171":132,"172":131,"173":129,"174":129,"175":129,"176":130,"177":129,"178":129,"179":128,"180":129,"181":132,"182":134,"183":135,"184":134,"185":133,"186":131,"187":131,"188":131,"189":132,"190":134,"191":134,"192":134,"193":134,"194":137,"195":140,"196":142,"197":142,"198":141,"199":138,"200":136,"201":135,"202":137,"203":138,"204":137,"205":135,"206":134,"207":137,"208":142,"209":147,"210":148,"211":147,"212":146,"213":144,"214":144,"215":144,"216":144,"217":142,"218":138,"219":136,"220":137,"221":141,"222":145,"223":149,"224":150,"225":150,"226":150,"227":150,"228":150,"229":148,"230":145,"231":142,"232":142,"233":144,"234":146,"235":146,"236":146,"237":147,"238":150,"239":153,"240":153,"241":149,"242":145,"243":143,"244":141,"245":141,"246":142,"247":143,"248":143,"249":142,"250":144,"251":148,"252":153,"253":152,"254":142,"255":130,"256":123,"257":123,"258":127,"259":130,"260":132,"261":134,"262":139,"263":147,"264":154,"265":155,"266":148,"267":134,"268":119,"269":108,"270":106,"271":110,"272":115,"273":119,"274":124,"275":129,"276":136,"277":141,"278":141,"279":135,"280":125,"281":115,"282":108,"283":105,"284":105,"285":108,"286":111,"287":115,"288":119,"289":122,"290":121,"291":116,"292":110,"293":106,"294":104,"295":101,"296":98,"297":96,"298":98,"299":103,"300":110,"301":115,"302":116,"303":112,"304":104,"305":98,"306":95,"307":95,"308":94,"309":91,"310":88,"311":88,"312":94,"313":101,"314":107,"315":110,"316":107,"317":103,"318":100,"319":99,"320":99,"321":98,"322":95,"323":89,"324":87,"325":89,"326":96,"327":103,"328":107,"329":109,"330":110,"331":111,"332":113,"333":113,"334":110,"335":105,"336":102,"337":102,"338":104,"339":105,"340":107,"341":110,"342":115,"343":120,"344":123,"345":123,"346":122,"347":120,"348":120,"349":121,"350":123,"351":124,"352":123,"353":122,"354":122,"355":126,"356":133,"357":137,"358":136,"359":132,"360":128,"361":129,"362":134,"363":139,"364":139,"365":135,"366":131,"367":131,"368":135,"369":141,"370":144,"371":143,"372":140,"373":138,"374":138,"375":140,"376":142,"377":140,"378":136,"379":131,"380":130,"381":133,"382":138,"383":141,"384":141,"385":140,"386":140,"387":140,"388":139,"389":136,"390":132,"391":129,"392":128,"393":128,"394":129,"395":131,"396":133,"397":135,"398":136,"399":136,"400":135,"401":132,"402":129,"403":125,"404":123,"405":123,"406":125,"407":126,"408":126,"409":126,"410":128,"411":131,"412":133,"413":133,"414":130,"415":127,"416":125,"417":125,"418":125,"419":125,"420":125,"421":125,"422":125,"423":126,"424":129,"425":131,"426":132,"427":131,"428":128,"429":126,"430":126,"431":128,"432":129,"433":130,"434":130,"435":130,"436":132,"437":134,"438":136,"439":135,"440":133,"441":131,"442":129,"443":128,"444":129,"445":130,"446":132,"447":134,"448":136,"449":138,"450":140,"451":142,"452":143,"453":142,"454":140,"455":137,"456":135,"457":134,"458":134,"459":134,"460":134,"461":135,"462":137,"463":139,"464":143,"465":147,"466":148,"467":147,"468":146,"469":145,"470":144,"471":141,"472":139,"473":137,"474":136,"475":137,"476":139,"477":142,"478":145,"479":149,"480":150,"481":151,"482":152,"483":152,"484":151,"485":146,"486":141,"487":138,"488":140,"489":145,"490":147,"491":146,"492":145,"493":147,"494":152,"495":157,"496":156,"497":151,"498":145,"499":140,"500":137,"501":139,"502":143,"503":147,"504":147,"505":144,"506":143,"507":146,"508":152,"509":152,"510":143,"511":129}';

※ If we draw this data to canvas, we can see the below: (This is a sound of vowel 'i' (it sounds like 'ee'))

It seems 2 period of the wave is captured. Since length is 512, we can guess that data of one period is located at index 0 ~ 255.

(2) I processed the data.

const parsed = JSON.parse(raw);
const arrayfied = Array.from(parsed);
const sliced = arrayfied.slice(0, 256);
const refined = [];

// According to the Web Audio API specification,
// "The values stored in the unsigned byte array are computed in the following way.
// Let x[k] be the time-domain data. Then the byte value, b[k], is
// b[k]=⌊128(1+x[k])⌋." So, I manipulate the array like the following:

for (let i = 0; i < sliced.length; i++) {
  refined[i] = (sliced[i] / 128) - 1;
}

(3) I calculated Fourier coefficients.

// This function calculates Riemann sum (area approximation using rectangles)
// fn: function to be calculated
// initial: calculation start point
// final: calculation end point
// division: number of rectangles to use
// nth: used for an, bn (please see below)
function numerical_integration(fn, initial, final, division, nth = null) {
  let accumulation = 0;
  const STEP = (final - initial) / division;

  for (let i = initial; i <= final; i++) {
    // calculate an area of a rectangle and add
    accumulation += fn(i, initial, final, nth) * STEP;
  }

  return accumulation;
}

// This is f(t)
function f0(t) {
  const result = refined[t];

  return result;
}

// This is f(t) * cos(nwt)
// ※ w = 2 * Math.PI / period
function fc(t, i, f, n) {
  const result = f0(t) * Math.cos(n * 2 * Math.PI * t / (f - i));

  return result;
}

// This is f(t) * sin(nwt)
function fs(t, i, f, n) {
  const result = f0(t) * Math.sin(n * 2 * Math.PI * t / (f - i));

  return result;
}

// This function returns a0 value
// period is 256 (0 ~ 255) and the last element of array refined is at index 255,
// so I subtract one.
function getA0(period) {
  const result = numerical_integration(f0, 0, period - 1, 100) / period;

  return result;
}

// This function returns an values
function getAn(period) {
  const result = [];

  for (let i = 1; i <= 49; i++) {
    result.push(numerical_integration(fc, 0, period - 1, 100, i) * 2 / period);
  }

  return result;
}

// This function returns bn values
function getBn(period) {
  const result = [];

  for (let i = 1; i <= 49; i++) {
    result.push(numerical_integration(fs, 0, period - 1, 100, i) * 2 / period);
  }

  return result;
}

So far so good! Now we can check whether our Fourier coefficients are well calculated by making a wave function using the coefficients and drawing it to canvas!

const a0 = getA0(refined.length);
const an = getAn(refined.length);
const bn = getBn(refined.length);

// returns y coordinate
function getY(t) {
  let anSum = 0;
  let bnSum = 0;

  for (let i = 0; i <= 48; i++) {
    anSum += an[i] * Math.cos((i + 1) * 2 * Math.PI * t / refined.length);
    bnSum += bn[i] * Math.sin((i + 1) * 2 * Math.PI * t / refined.length);
  }

  const result = a0 + anSum + bnSum;

  return result;
}

// draw
canvasContext.lineTo(x, getY(t));

Wow! Nicely done! It is nearly as same as the original wave!

Then you might ask "So, what is your question?" Therefore, I'm going to ask my question: How to reproduce sound by using Fourier coefficients? (I do not know much about Web Audio API and digital sound)

What I've thought is three things:

Maybe AudioBuffer?
AudioWorklet?
PeriodicWave and OscillatorNode?

I tried AudioWorklet but it sounded like saturated(?) A4(perhaps) with crackle 'tick tick' sound. The AudioWorklet code is as follows:

class IWaveProducer extends AudioWorkletProcessor {
  constructor() {
    super();

    this.t = 0;
  }

  process(inputs, outputs, parameters) {
    const output = outputs[0];

    output.forEach(channel => {
      for (let i = 0; i < channel.length; i++) {
        channel[i] = getY(this.t);
      }
    });

    this.t++;

    return true;
  }
}

registerProcessor('i-wave-producer', IWaveProducer);

And this is the graph:

So this time I tried PeriodicWave and OscillatorNode but it also failed. The code is as follows:

const real = new Float32Array(50);
const imag = new Float32Array(50);

real[0] = a0;
imag[0] = 0;

for (let i = 1; i <= 48; i++) {
  real[i + 1] = an[i];
  imag[i + 1] = bn[i];
}

const wave = new PeriodicWave(audioCtx, { real, imag, disableNormalization: false });
const osc = new OscillatorNode(audioCtx, { periodicWave: wave });

osc.connect(analyser)
   .connect(audioCtx.destination);
osc.start();

And this is the graph:

It sounded like a A4 sawtooth wave(perhaps). Also, interestingly, it seems all the data is inserted correctly, since the form of the wave is quite similar to the above picture (please see 'waveform approximated' picture). (Its pattern: one high mountain and one small mountain)

...But this is totally not I want! What I want is to reproduce a vowel 'i' sound! How can I achieve my goal? Please let me know if you know something. It would be greatly appreciated. I'm curious to death. Please help me ㅠㅠ. Thank you very much for reading this long question.

Or is it impossible to make 'voice' with Web Audio API? But I've seen a library making voice using JavaScript before. For example:

Hi again! I think just found the answer! The answer is... 「AudioBuffer」. I'm literally crying...with delight... Anyway, here is the code!!!

// Since the length of wave is 256
// and I guess (maybe wrong) that it means
// this wave lasts for 256 / 44100 seconds (= 0.0058).
// Thus, in order to make it longer,
// multiply 1000. So this sound will exist for 5.8 seconds.
// (Since sampling rate is 44100 per sec,
// the formula results in the length of this buffer--256000.)
const audioBuffer = new AudioBuffer({ numberOfChannels: 1, length: 1000 * audioCtx.sampleRate * 256 / 44100, sampleRate: audioCtx.sampleRate });

const buffering = audioBuffer.getChannelData(0);
let count = 0;

for (let i = 0; i < audioBuffer.length; i++) {
  buffering[i] = refined[count];

  if (count === 255) {
    count = 0;
  } else {
    count++;
  }
}

const source = new AudioBufferSourceNode(audioCtx, { buffer: audioBuffer });
  
source.connect(analyser)
      .connect(audioCtx.destination);

source.start();

The resulting sound is a bit hilarious! But I think it surely sounds like 'i (ee)'. It also sounds like 'fa' note. Why is that? Let's think about it together. First I think we need to calculate the wave's frequency. Since the wave's one period is 0.0058 seconds, thus the frequency is 1 / 0.0058, which is 172.4138 Hz.

Next, A4 is 440 Hz. Therefore A3 is 220Hz. Four notes below is F3 (A3, G#4, G4, F#3, F3). Then the frequency of F3 is 220 * 2^(-4/12) = 174.6141 Hz.

172 is nearly same with 174. !!!!! Which so absolutely makes sense! The secret is now solved. That's why that sound sounds like fa.

Thank you for reading my tough, but at the same time beautiful fighting story against Web Audio API. Bye!

Hi again again! I've just found that PeriodicWave and OscillatorNode can also be the answer!

const osc = new OscillatorNode(audioCtx, { periodicWave: wave, frequency: 174 });

Setting the frequency parameter is the key! Bye again!

Then the only one left is AudioWorklet. Can it be also the answer? It makes me curious.

ANSWER

Answered 2022-Feb-04 at 23:39

In golang I have taken an array ARR1 which represents a time series ( could be audio or in my case an image ) where each element of this time domain array is a floating point value which represents the height of the raw audio curve as it wobbles ... I then fed this floating point array into a FFT call which returned a new array ARR2 by definition in the frequency domain where each element of this array is a single complex number where both the real and the imaginary parts are floating points ... when I then fed this array into an inverse FFT call ( IFFT ) it gave back a floating point array ARR3 in the time domain ... to a first approximation ARR3 matched ARR1 ... needless to say if I then took ARR3 and fed it into a FFT call its output ARR4 would match ARR2 ... essentially you have this time_domain_array --> FFT call -> frequency_domain_array --> InverseFFT call -> time_domain_array ... rinse N repeat

I know Web Audio API has a FFT call ... do not know whether it has an IFFT api call however if no IFFT ( inverse FFT ) you can write your own such function here is how ... iterate across ARR2 and for each element calculate the magnitude of this frequency ( each element of ARR2 represents one frequency and in the literature you will see ARR2 referred to as the frequency bins which simply means each element of the array holds one complex number and as you iterate across the array each successive element represents a distinct frequency starting from element 0 to store frequency 0 and each subsequent array element will represent a frequency defined by adding incr_freq to the frequency of the prior array element )

Each index of ARR2 represents a frequency where element 0 is the DC bias which is the zero offset bias of your input ARR1 curve if its centered about the zero crossing point this value is zero normally element 0 can be ignored ... the difference in frequency between each element of ARR2 is a constant frequency increment which can be calculated using

incr_freq := sample_rate / number_of_samples  //  with sample_rate of 44100 samples per second, and one second worth of samples ( 44100 )
                                              //  this gives you a frequency increment resolution of 1 Hertz ... IE each freq bin is 1 Hertz apart

For a given element of ARR2 you need to calculate the magnitude using

curr_real = real(curr_complex) // pluck out real portion of imaginary number
curr_imag = imag(curr_complex) // ditto for im

curr_mag = 2.0 * math.Sqrt(curr_real*curr_real+curr_imag*curr_imag) / number_of_samples  // magnitude of this freq

curr_theta = math.Atan2(curr_imag, curr_real)  //  phase of this frequency

At this point you are iterating across ARR2 and inside this loop you are doing above magnitude and phase calculation for each element of ARR2 ... now simply synthesize a sine curve for each frequency now that you know both the magnitude and phase ... remember as you iterate across ARR2 you are incrementing by the above mentioned incr_freq ... then simply combine each of these freshly synthesized sine curves into a single output curve and stow into a new ARR3 which will match your original source ARR1

Have fun and good luck !!!

UPDATE The notion of window refers to a set of audio samples ... say you have an input WAV format file from which you open up and iterate across its raw audio curve ... if this WAV file holds a 10 minute song if you feed the entire audio into one FFT call the result will represent the entire file however if you instead chop the entire set of audio samples ( these are just points on the raw audio curve ) into several windows where each window is only say 1024 such audio samples and feed each of these windows of samples into a FFT call each output from FFT call will be specific to only that portion of the song ... when you use a tool like Audacity to play a song while you view its real time FFT spectrum that is showing you a refreshed view of the current window as Audacity chops the input audio into a new window very 1024 or so audio samples

Source https://stackoverflow.com/questions/70974735

QUESTION

Get Latency of Bluetooth Headphoners UWP C++

Asked 2022-Jan-18 at 09:08

I want to make sure the latency between my app and the bluetooth headphones is accounted for, but I have absolutely no idea how I can get this value. The closest thing I found was: BluetoothLEPreferredConnectionParameters.ConnectionLatency which is only available on Windows 11... Otherwise there isn't much to go on.

Any help would be appreciated.

Thanks, Peter

ANSWER

Answered 2022-Jan-18 at 09:08

It's very difficult to get the exact latency because it is affected by many parameters - but you're on the right track by guessing that the connection parameters are a factor of this equation. I don't have much knowledge on UWP, but I can give you the general parameters that affect the speed/latency, and then you can check their availability in the API or even contact Windows technical team to see if these are supported.

When you make a connection with a remote device, the following factors impact the speed/latency of the connection:-

Connection Interval: this specifies the interval at which the packets are sent during a connection. The lower the value, the higher the speed. The minimum value as per the Bluetooth spec is 7.5ms.
Slave Latency: this is the value you originally mentioned - it specifies the number of packets that can be missed before a connection is considered lost. A value of 0 means that you have the fastest most robust connection.
Connection PHY: this is the modulation on which the packets are sent. If both devices support 2MPHY, then the connection should be quicker.
Data Length/MTU Extension: these are two separate features but I am looping them together becuase the effect is the same - more bytes are sent per packet, which results in a higher throughput. The maximum value is 251 bytes per packet.

You can find more information about these parameters here:-

And below are some other links that might help you understand what is supported on UWP:-

Source https://stackoverflow.com/questions/70742321

QUESTION

Loading Wave File but there is random nonsense at the end of the data rather than the expected samples

Asked 2022-Jan-11 at 19:43

I've got a simple wav header reader i found online a long time ago, i've gotten back round to using it but it seems to replace around 1200 samples towards the end of the data chunk with a single random repeated number, eg -126800. At the end of the sample is expected silence so the number should be zero.

Here is the simple program:

void main() {
    WAV_HEADER* wav = loadWav(".\\audio\\test.wav");
    double sample_count = wav->SubChunk2Size * 8 / wav->BitsPerSample;

    printf("Sample count: %i\n", (int)sample_count);

    vector<int16_t> samples = vector<int16_t>();

    for (int i = 0; i < wav->SubChunk2Size; i++)
    {
        int val = ((wav->data[i] & 0xff) << 8) | (wav->data[i + 1] & 0xff);
        samples.push_back(val);
    }
    printf("done\n");
}

And here is the Wav reader:

typedef struct
{
    //riff
    uint32_t Chunk_ID;
    uint32_t ChunkSize;
    uint32_t Format;

    //fmt
    uint32_t SubChunk1ID;
    uint32_t SubChunk1Size;
    uint16_t AudioFormat;
    uint16_t NumberOfChanels;
    uint32_t SampleRate;
    uint32_t ByteRate;

    uint16_t BlockAlignment;
    uint16_t BitsPerSample;

    //data
    uint32_t SubChunk2ID;
    uint32_t SubChunk2Size;

    //Everything else is data. We note it's offset
    char data[];

} WAV_HEADER;
#pragma pack()

inline WAV_HEADER* loadWav(const char* filePath)
{
    long size;
    WAV_HEADER* header;
    void* buffer;

    FILE* file;

    fopen_s(&file,filePath, "r");
    assert(file);

    fseek(file, 0, SEEK_END);
    size = ftell(file);
    rewind(file);

    std::cout << "Size of file: " << size << std::endl;

    buffer = malloc(sizeof(char) * size);
    fread(buffer, 1, size, file);

    header = (WAV_HEADER*)buffer;

    //Assert that data is in correct memory location
    assert((header->data - (char*)header) == sizeof(WAV_HEADER));

    //Extra assert to make sure that the size of our header is actually 44 bytes
    assert((header->data - (char*)header) == 44);

    fclose(file);

    return header;
}

Im not sure what the problem is, i've confirmed that there is no meta data, nor is there a mis match between the numbers read from the header of the file and the actual file. Im assuming its a size/offset misallignment on my side, but i cannot see it. Any help welcomed. Sulkyoptimism

ANSWER

Answered 2022-Jan-07 at 21:55

WAV is just a container for different audio sample formats.

You're making assumptions on a wav file that would have been OK on Windows 3.11 :) These don't hold in 2021.

Instead of rolling your own Wav file reader, simply use one of the available libraries. I personally have good experiences using libsndfile, which has been around roughly forever, is very slim, can deal with all prevalent WAV file formats, and with a lot of other file formats as well, unless you disable that.

This looks like a windows program (one notices by the fact you're using very WIN32API style capital struct names – that's a bit oldschool); so, you can download libsndfile's installer from the github releases and directly use it in your visual studio (another blind guess).

Source https://stackoverflow.com/questions/70627117

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