TTS | 🐸💬 - a deep learning toolkit for Text-to-Speech | Speech library
kandi X-RAY | TTS Summary
kandi X-RAY | TTS Summary
Underlined "TTS*" and "Judy*" are TTS models.
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Top functions reviewed by kandi - BETA
- Train the model .
- Integrate quadratic spline .
- Compute speech synthesis .
- convert number to Chinese
- Generate matplotlib plot .
- Transfers audio to a specific speaker .
- Perform a single step .
- Loads TTS samples .
- Discretized mixture logistic loss .
- Setup the generator .
TTS Key Features
TTS Examples and Code Snippets
//SPEECH TO TEXT DEMO
speechToText.setOnClickListener({ view ->
Snackbar.make(view, "Speak now, App is listening", Snackbar.LENGTH_LONG)
.setAction("Action", null).show()
TranslatorFactory
.
$ examples/tts.py --output-device 11 --output-wav data/audio/tts_test
> The weather tomorrow is forecast to be warm and sunny with a high of 83 degrees.
Run 0 -- Time to first audio: 1.820s. Generated 5.36s of audio. RTFx=2.95.
Run 1 -- Time to
CUDA_VISIBLE_DEVICES=0 python UnetTTS_syn.py
from UnetTTS_syn import UnetTTS
models_and_params = {"duration_param": "train/configs/unetts_duration.yaml",
"duration_model": "models/duration4k.h5",
"acous_param
def aggregate_global_cache(self, global_tt_summary_cache):
"""Merges the given caches on tpu.
Args:
global_tt_summary_cache: The global tensor tracer summary cache tensor
with shape (num_cores, num_traced_tensors, num_traced_si
@Override
public String render(Type type, List args, SessionFactoryImplementor factory) throws QueryException {
if (args == null || args.size() != 3) {
throw new IllegalArgumentException("The function must be passed 2 arguments");
}
Strin
paths = {
"chrome": ['open', '/Applications/Google Chrome.app'],
"excel": ['open', '/System/Applications/Microsoft Excel.app'],
"calculator": ['open', '/System/Applications/Calculator.app'],
}
In some cases, it might help your audience to slow
the speaking rate slightly to aid in comprehension.
or
In some cases, it might help your audience to slow
the speaking rate slightly to aid in comprehension.
for singlepaper in paperResults:
paperyear = singlepaper.find(class_="datePublished")
print(paperyear)
for singlepaper in paperResults:
paperyear = singlepaper.find('span', itemprop="datePublished")
out = df.groupby('DAY')[['TTM','TTS']].mean().add_prefix('mean').reset_index()
DAY meanTTM meanTTS
0 20210101 0.1 0.3
1 20210102 0.3 0.4
Community Discussions
Trending Discussions on TTS
QUESTION
I wanted to make a command for my bot that returns the user avatar, but I am getting an error:
...ANSWER
Answered 2022-Mar-27 at 19:10Collection#map
returns an array and you try to send
that. As you can only send a string, you can join the returned array using the Array#join
method:
QUESTION
There are two servers that I'm testing on, and on one server, the bot works, but the bot does not work on another server.
However, the ping command works
The command that makes the bot crash on only one server, while it works on another server
...ANSWER
Answered 2022-Mar-08 at 07:35This means that your bot is missing permissions to (presumably) send messages on that server.
You can prevent it from crashing by adding a .catch
statement after sending the message like this:
QUESTION
i'm getting an error whenever I try to send an embed. This has only just started happening, and i've not done any form of updates (as far as I know) Here's my code:
...ANSWER
Answered 2022-Feb-27 at 18:54With the newest update to Discords API your final line should be changed to this:
QUESTION
After updating lifecycle
library to 2.4.0 Android studio marked all Lifecycle events as deprecated.
ANSWER
Answered 2021-Dec-16 at 18:53It's deprecated because they now expect you to use Java 8 and implement the interface DefaultLifecycleObserver. Since Java 8 allows interfaces to have default implementations, they defined DefaultLifecycleObserver with empty implementations of all the methods so you only need to override the ones you use.
The old way of marking functions with @OnLifecycleEvent
was a crutch for pre-Java 8 projects. This was the only way to allow a class to selectively choose which lifecycle events it cared about. The alternative would have been to force those classes to override all the lifecycle interface methods, even if leaving them empty.
In your case, change your class to implement DefaultLifecycleObserver and change your functions to override the applicable functions of DefaultLifecycleObserver. If your project isn't using Java 8 yet, you need to update your Gradle build files. Put these in the android
block in your module's build.gradle
:
QUESTION
I'm quite new to AI and I'm currently developing a model for non-parallel voice conversions. One confusing problem that I have is the use of vocoders.
So my model needs Mel spectrograms as the input and the current model that I'm working on is using the MelGAN vocoder (Github link) which can generate 22050Hz Mel spectrograms from raw wav files (which is what I need) and back. I recently tried WaveGlow Vocoder (PyPI link) which can also generate Mel spectrograms from raw wav files and back.
But, in other models such as, WaveRNN , VocGAN , WaveGrad There's no clear explanation about wav to Mel spectrograms generation. Do most of these models don't require the wav to Mel spectrograms feature because they largely cater to TTS models like Tacotron? or is it possible that all of these have that feature and I'm just not aware of it?
A clarification would be highly appreciated.
...ANSWER
Answered 2022-Feb-01 at 23:05Check e.g. this part of the MelGAN code: https://github.com/descriptinc/melgan-neurips/blob/master/mel2wav/modules.py#L26
Specifically, the Audio2Mel
module simply uses standard methods to create log-magnitude mel spectrograms like this:
- Compute the STFT by applying the Fourier transform to windows of the input audio,
- Take the magnitude of the resulting complex spectrogram,
- Multiply the magnitude spectrogram by a mel filter matrix. Note that they actually get this matrix from
librosa
! - Take the logarithm of the resulting mel spectrogram.
Your confusion might stem from the fact that, usually, authors of Deep Learning papers only mean their mel-to-audio "decoder" when they talk about "vocoders" -- the audio-to-mel part is always more or less the same. I say this might be confusing since, to my understanding, the classical meaning of the term "vocoder" includes both an encoder and a decoder.
Unfortunately, these methods will not always work exactly in the same manner as there are e.g. different methods to create the mel filter matrix, different padding conventions etc.
For example, librosa.stft
has a center
argument that will pad the audio before applying the STFT, while tensorflow.signal.stft
does not have this (it would require manual padding beforehand).
An example for the different methods to create mel filters would be the htk
argument in librosa.filters.mel
, which switches between the "HTK" method and "Slaney". Again taking Tensorflow as an example, tf.signal.linear_to_mel_weight_matrix
does not support this argument and always uses the HTK method. Unfortunately, I am not familiar with torchaudio
, so I don't know if you need to be careful there, as well.
Finally, there are of course many parameters such as the STFT window size, hop length, the frequencies covered by the mel filters etc, and changing these relative to what a reference implementation used may impact your results. Since different code repositories likely use slightly different parameters, I suppose the answer to your question "will every method do the operation(to create a mel spectrogram) in the same manner?" is "not really". At the end of the day, you will have to settle for one set of parameters either way...
Bonus: Why are these all only decoders and the encoder is always the same?The direction Mel -> Audio is hard. Not even Mel -> ("normal") spectrogram is well-defined since the conversion to mel spectrum is lossy and cannot be inverted. Finally, converting a spectrogram to audio is difficult since the phase needs to be estimated. You may be familiar with methods like Griffin-Lim (again, librosa has it so you can try it out). These produce noisy, low-quality audio. So the research focuses on improving this process using powerful models.
On the other hand, Audio -> Mel is simple, well-defined and fast. There is no need to define "custom encoders".
Now, a whole different question is whether mel spectrograms are a "good" encoding. Using methods like variational autoencoders, you could perhaps find better (e.g. more compact, less lossy) audio encodings. These would include custom encoders and decoders and you would not get away with standard librosa functions...
QUESTION
I'm trying to use Web Speech API to read text on my web page. But I found that some of the SAPI5 voices installed in my Windows 10 would not show up in the output of speechSynthesis.getVoices()
, including the Microsoft Eva Mobile
on Windows 10 "unlock"ed by importing a registry file. These voices could work fine in local TTS programs like Balabolka
but they just don't show in the browser. Are there any specific rules by which the browser chooses whether to list the voices or not?
ANSWER
Answered 2021-Dec-31 at 08:19OK, I found out what was wrong. I was using Microsoft Edge and it seems that Edge only shows some of Microsoft voices. If I use Firefox, the other installed voices will also show up. So it was Edge's fault.
QUESTION
I'm trying to build a simple Discord bot which finds information about a specific stock when its name or symbol is inputted by the user. I included my code which web-scraped all the data into another document, but it's included in my bot.py
file. I have it set up so that when I type viewall
, a list of all the stocks should appear. However, when typing that command in my Discord server, I get nothing. However, the output on my terminal is:
ANSWER
Answered 2021-Dec-31 at 04:09This is just my guess, but maybe variable response is not detected as a string. What you may want to try:
QUESTION
I am trying to write an object detection + text-to-speech code to detect objects and produce a voice output on the raspberry pi 4. However, as of right now, I am trying to write a simple python script that incorporates both elements into a single .py file and preferably as a function. I will then run this script on the raspberry pi. I want to give credit to Murtaza's Workshop "Object Detection OpenCV Python | Easy and Fast (2020)" and https://pypi.org/project/pyttsx3/ for the Text to speech documentation for pyttsx3. I have attached the code below. I have tried running the program and I always keep getting errors with the Text to speech code (commented lines 33-36 for reference). I believe it is some looping error but I just can't seem to get the program to run continuously. For instance, if I run the code without the TTS part, it works fine. Otherwise, it runs for perhaps 3-5 seconds and suddenly stops. I am a beginner but highly passionate in computer vision, and any help is appreciated!
...ANSWER
Answered 2021-Dec-28 at 16:46I installed pyttsx3 using the two commands in the terminal on the Raspberry Pi:
- sudo apt update && sudo apt install espeak ffmpeg libespeak1
- pip install pyttsx3
I followed the video youtube.com/watch?v=AWhDDl-7Iis&ab_channel=AiPhile to install pyttsx3. My functional code should also be listed above. My question should be resolved but hopefully useful to anyone looking to write a similar program. I have made minor tweaks to my code.
QUESTION
Hi so essentially I'm writing an application that should provide a GUI along with speech recognition commands and the program should answer in TTS. I wrote a little test program because I wanted to learn threading with pyQt5 as it is needed to keep the GUI responsive - that's my understanding so far and it seems to work unless it tries to TTS.
Now I have the problem that as long as I don't TTS the input, everything works fine. But with pyttsx3, the .runAndWait() function exits the execution of my code. This is the code in question: (The GUI has the slider to check if the threading works)
...ANSWER
Answered 2021-Dec-17 at 23:14Ok, I was able to work around the problem myself. It was in fact the runAndWait() function from pyttsx3 that was breaking the program. Instead, I now use a combination of gTTS, pydub, soundfile, playsound, and pyrubberband.
The speak function now looks like this:
QUESTION
I have developed a workout app. I've two timers on the screen one is for the total timer and one for exercise time also some tts and MediaPlayer sounds. When the screen is locked my exercise timer is stuck after 10 seconds but my total remaining time timer is still running. So confused about why is it happening, I've verified battery optimization permission on\off but the issue is still the same. I've set a toast in tick function and I turn off the screen when I come back toast is showing but my timer is stuck. Can anyone help to get out of this? Thanks in advance. Countdown works fines when the screen is opened or connected to the charger.
Exercise Timer code below... ...ANSWER
Answered 2021-Dec-07 at 06:31Your activity is getting stopped or destroyed and that's why your timer gets stuck. To keep the timer running even if the app is closed or killed, see this way:-
You can use this technique to detect how long the user was inactive (even when the app is in the background).
- Create a
SharedPreference
& its Editor object. Then declare 3 long variables such:
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