malarinv
/
plume-asr
mirror of https://github.com/malarinv/plume-asr.git
1
0
Fork 0
Code Issues Releases Wiki Activity
15 Commits
2 Branches
0 Tags
423 KiB
Jupyter Notebook 54.8%
Python 43.3%
HTML 1.9%
 
 
 
Go to file
Malar e07c7c9caf 1. refactor package root to src/ layout 
2. add framwork suffix for models
3. change black max columns to 79
4. add tests
5. integrate vad, encrypt and  refactor manifest, regentity, extended_path, audio, parallel utils
6. added ui utils for encrypted preview
7. wip marblenet model
8. added transformers based wav2vec2 inference
9. update readme and manifest
10. add deploy setup target
 		2021-06-03 11:30:08 +05:30
src/plume 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
tests/plume 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
.flake8 1. refactored ui_dump 2020-08-09 19:16:35 +05:30
.gitignore 1. integrated data generator using google tts 2020-07-14 12:09:46 +05:30
LICENSE Initial commit 2020-03-16 14:21:51 +05:30
MANIFEST.in 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
Notes.md massive refactor/rename to plume 2021-02-23 19:43:33 +05:30
README.md 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
pyproject.toml 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
setup.py 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30
tox.ini 1. refactor package root to src/ layout 2021-06-03 11:30:08 +05:30

README.md

Plume ASR

image

Generates text from audio containing speech

Table of Contents

Prerequisites

# apt install libsndfile-dev ffmpeg

Features

Installation

To install the packages and its dependencies run.

python setup.py install

or with pip

pip install .[all]

The installation should work on Python 3.6 or newer. Untested on Python 2.7

Usage

Library

Jasper

from plume.models.jasper_nemo.asr import JasperASR
asr_model = JasperASR("/path/to/model_config_yaml","/path/to/encoder_checkpoint","/path/to/decoder_checkpoint") # Loads the models
TEXT = asr_model.transcribe(wav_data) # Returns the text spoken in the wav

Wav2Vec2

from plume.models.wav2vec2.asr import Wav2Vec2ASR
asr_model = Wav2Vec2ASR("/path/to/ctc_checkpoint","/path/to/w2v_checkpoint","/path/to/target_dictionary") # Loads the models
TEXT = asr_model.transcribe(wav_data) # Returns the text spoken in the wav

Command Line

$ plume

Pretrained Models

Jasper https://ngc.nvidia.com/catalog/models/nvidia:multidataset_jasper10x5dr/files?version=3 Wav2Vec2 https://github.com/pytorch/fairseq/blob/master/examples/wav2vec/README.md