AutoEq | Automatic headphone equalization from frequency responses | Audio Utils library

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

have you tried using javascript for audio? such as

You can try this. Here you have to provide audio file source instead of image source. I did not try this code, But i assure you to it should work!

https://www.codegrepper.com/code-examples/javascript/javascript+download+image+from+url

What you are seeing is indeed the expected outcome of an FFT (Fourier Transform). The logarithmic f-axis that you're expecting is achieved by the Constant-Q transform.

Now, the implementation of the Constant-Q transform is non-trivial. The Fourier Transform has become popular precisely because there is a fast implementation (the FFT). In practice, the constant-Q transform is often implemented by using an FFT, and combining multiple high-frequency bins. This discards resolution in the higher bins; it doesn't give you more resolution in the lower bins.

To get more frequency resolution in the lower bins of the FFT, just use a longer window. But if you also want to keep the time resolution, you'll have to use a hop size that's smaller than the window size. In other words, your FFT windows will overlap.

• 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

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

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:-

• A Practical Guide to BLE Throughput
• Maximizing BLE Throughput: Everything You Need to Know
• Bluetooth 5 Speed - How to Achieve Maximum Throughput

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

• Bluetooth Developer FAQ
• BluetoothLEConnectionParameters.OptimizedProperty
• Bluetooth LE Preferred Connection Parameter Class
• Bluetooth LE Connection PHY class
• How to Change MTU Size and PHY on Windows UWP C++

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).

I suppose it'll depend how you're building your application. Hard to help without much detail around specs. Though, here are a few options for you.

There are a few stream options, for example;

• mic

Or if you're using React;

• react-mic

Or if you're wanting to go real basic with some vanilla JS;

• Web Fundamentals: Recording Audio