deepspeech | A PyTorch implementation of DeepSpeech and DeepSpeech2 | Speech library
kandi X-RAY | deepspeech Summary
kandi X-RAY | deepspeech Summary
A PyTorch implementation of DeepSpeech and DeepSpeech2.
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Top functions reviewed by kandi - BETA
- Return a trained model
- Save the model to disk
- Get the path to the last state dict
- Return a dictionary of all state dictionaries
- Load all transcription files
- Processes an audio file
- Parse a transcription file
- Sort the paths by duration
- Train the model
- Return a function to clip gradients
- Log end of training
- Log a training step
- Calculate the checksum of a directory
- Calculate the checksum of a file
- Parse an algorithm
- Evaluate the model
- Evaluate the loss function
- Download the tarball of the dataset
- Check integrity of a subset
- Save a trained model
- Calculate the layer feature size
- Get argument parser
- Get a dev data loader
- Return a training data loader
- Return the decoder from the given arguments
- Calculate the output length
deepspeech Key Features
deepspeech Examples and Code Snippets
Lines of Code : 8License : Non-SPDX (NOASSERTION)
Copysum_edits = sum([edit_distance(target, predict)
for target, predict in zip(targets, predictions)])
sum_lens = sum([len(target) for target in targets])
WER = (1.0/N) * (sum_edits / sum_lens)
>>> (1.0/3) * ((1.0/1) + (2.0/4) deepspeech ds1 \
--state_dict_path $MODEL_PATH \
--log_file \
--decoder greedy \
--train_subsets \
--dev_log wer \
--dev_subsets dev-clean \
--dev_batch_size 1
make build
sudo docker run --runtime=nvidia --shm-size 512M -p 9999:9999 deepspeech
deepspeech --help
import deepspeech
Community Discussions
Trending Discussions on deepspeech
QUESTION
I am trying to make a speech to text system using raspberry pi. There are many problems with VAD. I am using DeepCpeech's VAD script. Adafruit I2S MEMS microphone accepts only 32-bit PCM audio. So I modified the script to record 32-bit audio and then convert it to 16 bit for DeepSpeech's processing. Frames generation and conversation parts are below:
...ANSWER
Answered 2022-Jan-26 at 13:36I searched for DeepCpeech's VAD script and found it. The problem is connected with the webrtcvad. The webrtcvad VAD only accepts 16-bit mono PCM audio, sampled at 8000, 16000, 32000 or 48000 Hz. So you need to convert the 32-bit frame to 16-bit (I am about PyAudio output frame) to process webrtcvad.is_speech(). I changed and it worked fine.
QUESTION
ANSWER
Answered 2021-Nov-25 at 03:10these errors are not related to DeepSpeech, they're related to ALSA, which is the sound subsystem for Linux. By the looks of the error, your system is having trouble accessing the microphone.
I would recommend running several ALSA tests, such as;
arecord -l
This should give you a list of recording devices that are detected, such as:
QUESTION
I am trying to build customised scorer (language model) for speech-to-text using DeepSpeech in colab. While calling generate_lm.py getting this error:
...ANSWER
Answered 2021-Dec-06 at 03:33Able to find a solution for the above question. Successfully created language model after reducing the value of top_k to 15000. My phrases file has about 42000 entries only. We have to adjust top_k value based on the number of phrases in our collection. top_k parameter says - this much of less frequent phrases will be removed before processing.
QUESTION
I am using below command to start the training of deepspeech model
...ANSWER
Answered 2021-Sep-25 at 18:12Following worked for me
Go to
QUESTION
During the build of lm binay to create scorer doe deepspeech model I was getting the following error again and again
...ANSWER
Answered 2021-Sep-25 at 14:09Following worked for me Go to
QUESTION
Getting following error when trying to excecute
...ANSWER
Answered 2021-Sep-23 at 07:59If i try it as below it worked fine.
QUESTION
so a part of my code is
...ANSWER
Answered 2021-Jun-13 at 13:29You have to install path provider package by running flutter pub add path_provider in your terminal. If you already installed it. check whether you are importing it to your file.
QUESTION
commands i used
...ANSWER
Answered 2021-May-26 at 00:07You are using wget to pull down a .whl file that was built for a different version of Python. You are pulling down
ds_ctcdecoder-0.9.3-cp36-cp36m-manylinux1_x86_64.whl
but are running Python 3.7. You need a different .whl file, such as:
ds_ctcdecoder-0.9.3-cp37-cp37m-manylinux1_x86_64.whl
This is available here from the DeepSpeech releases page on GitHub.
QUESTION
I am currently working on a project for which I am trying to use Deepspeech on a raspberry pi while using microphone audio, but I keep getting an Invalid Sample rate error. Using pyAudio I create a stream which uses the sample rate the model wants, which is 16000, but the microphone I am using has a sample rate of 44100. When running the python script no rate conversion is done and the microphones sample rate and the expected sample rate of the model produce an Invalid Sample Rate error.
The microphone info is listed like this by pyaudio:
...ANSWER
Answered 2021-Jan-09 at 16:47So after some more testing I wound up editing the config file for pulse. In this file you are able to uncomment entries which allow you to edit the default and/or alternate sampling rate. The editing of the alternative sampling rate from 48000 to 16000 is what was able to solve my problem.
The file is located here: /etc/pulse/daemon.conf .
We can open and edit this file on Raspberian using sudo vi daemon.conf.
Then we need to uncomment the line ; alternate-sample-rate = 48000 which is done by removing the ; and change the value of 48000 to 16000. Save the file and exit vim. Then restart the Pulseaudio using pulseaudio -k to make sure it runs the changed file.
If you are unfamiliar with vim and Linux here is a more elaborate guide through the process of changing the sample rate.
QUESTION
I’m training DeepSpeech from scratch (without checkpoint) with a language model generated using KenLM as stated in its doc. The dataset is a Common Voice dataset for Persian language.
My configurations are as follows:
- Batch size = 2 (due to cuda OOM)
- Learning rate = 0.0001
- Num. neurons = 2048
- Num. epochs = 50
- Train set size = 7500
- Test and Dev sets size = 5000
- dropout for layers 1 to 5 = 0.2 (also 0.4 is experimented, same results)
Train and val losses decreases through the training process but after a few epochs val loss does not decrease anymore. Train loss is about 18 and val loss is about 40.
The predictions are all empty strings at the end of the process. Any ideas how to improve the model?
...ANSWER
Answered 2021-May-11 at 14:02maybe you need to decrease learning rate or use a learning rate scheduler.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
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Install deepspeech
You can use deepspeech like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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