DeepSpeech runtime transcript NodeJs native client. Some examples and tests.
DeepSpeech is an open-source Speech-To-Text engine. Documentation for installation, usage, and training models are available on deepspeech.readthedocs.io.
You want to access DeepSpeech speech to text runtime transcription from a well formatted WAV file, using NodeJs. I tested two options:
-
Spawning, from your NodeJs main thread, an external DeepSpeech command line program. That's the simplest, dumb and slow way in terms of performances. In general, spawning an external process, catching his stdout is a trivial approach, but applicable all times you do not have better inter process communication options.
Example: deepSpeechTranscriptSpawn.js.
-
Using DeepSpeech native NodeJs client interface. That's a more performant way.
Example: deepSpeechTranscriptNative.js.
The example is very raugh, presuming the audio file is a "well formatted" WAV file. The audio file is just read in memory and the deepspeech
model.stt()API is called. Official examples repo contains audio examples that show how to validate WAV, and speeech processing from streaming / in-memory buffers.
DeepSpeech requires a 16bit 16 KHz mono WAV input audio file. To record such a file:
sudo apt install sox
sudo apt install mediainfo
rec -f S16_BE -r 16000 -c 1 my_recording.wav
mediainfo my_recording.wav
General
Complete name : my_recording.wav
Format : Wave
File size : 64.0 KiB
Duration : 2 s 48 ms
Overall bit rate mode : Constant
Overall bit rate : 256 kb/s
Audio
Format : PCM
Format settings : Little / Signed
Codec ID : 1
Duration : 2 s 48 ms
Bit rate mode : Constant
Bit rate : 256 kb/s
Channel(s) : 1 channel
Sampling rate : 16.0 kHz
Bit depth : 16 bits
Stream size : 64.0 KiB (100%)
-
Install DeepSpeech
# Create and activate a virtualenv virtualenv -p python3 $HOME/tmp/deepspeech-venv/ source $HOME/tmp/deepspeech-venv/bin/activate # Install DeepSpeech pip3 install deepspeech # Download pre-trained English model files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models.pbmm curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models.scorer mkdir models mv *.pbmm *.scorer models/ # Download example audio files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/audio-0.9.3.tar.gz tar xvf audio-0.9.3.tar.gz # Transcribe an audio file deepspeech --model models/deepspeech-0.9.3-models.pbmm --scorer models/deepspeech-0.9.3-models.scorer --audio audio/2830-3980-0043.wav
-
Install this repo
git clone https://solyarisoftware/deepspeeechjs && cd deepspeeechjs
-
Install the official DeepSpeech npm package
npm install deepspeech
The bash script test_elapsed.sh compares elapsed times
of transcript of the audio file ./audio/4507-16021-0012.wav
(corresponding to text why should one halt on the way), in 3 cases:
- using a bash script running the CLI
deepspeechofficial client deepspeech_cli.sh - using the nodejs "spawn" client deepSpeechTranscriptSpawn.js
- using the nodejs native client deepSpeechTranscriptNative.js
(deepspeech-venv) $ test_elapsed.sh
deepspeech_cli
Loading model from file models/deepspeech-0.9.3-models.pbmm
TensorFlow: v2.3.0-6-g23ad988
DeepSpeech: v0.9.3-0-gf2e9c85
2021-01-31 11:04:53.878150: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Loaded model in 0.0121s.
Loading scorer from files models/deepspeech-0.9.3-models.scorer
Loaded scorer in 0.000152s.
Running inference.
why should one halt on the way
Inference took 1.527s for 2.735s audio file.
real 0m1,798s
user 0m2,483s
sys 0m0,495s
deepSpeechTranscriptSpawn
why should one halt on the way
real 0m1,832s
user 0m2,509s
sys 0m0,544s
deepSpeechTranscriptNative
usage: node deepSpeechTranscriptNative [<model pbmm file>] [<model scorer file>] [<audio file>]
using: node deepSpeechTranscriptNative ./models/deepspeech-0.9.3-models.pbmm ./models/deepspeech-0.9.3-models.scorer ./audio/4507-16021-0012.wav
TensorFlow: v2.3.0-6-g23ad988
DeepSpeech: v0.9.3-0-gf2e9c85
2021-01-31 11:05:01.371379: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
pbmm : ./models/deepspeech-0.9.3-models.pbmm
scorer : ./models/deepspeech-0.9.3-models.scorer
elapsed : 11ms
audio file: ./audio/4507-16021-0012.wav
transcript: why should one halt on the way
elapsed : 1553ms
real 0m1,669s
user 0m1,928s
sys 0m0,103s
As expected, the native client transcript elapsed time (1553ms), is much better than the spawn client (1832ms).
IMPORTANT: unfortunately npm package deepspeech cause a crash using node version 16.0.0.
See issue.
To run this project you have to downgrade installed Node version.
By example I had success with Node version 14.16.1.
- 0.0.9 test script testPerformances.sh improved
- The project is in a very draft stage.
- Add a better high-level API interface. E.g. including metadata as parameters
- Add a web server architectue. See: How to use DeepSpeech for a text-to-speech server (in NodeJs)
MIT (c) Giorgio Robino