Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together

Related tags

Text Data & NLPSpeechMix
Overview

SpeechMix

Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together.

Introduction

For the same input:

from datasets import load_dataset
import soundfile as sf


# define function to read in sound file
def map_to_array(batch):
    speech, _ = sf.read(batch["file"])
    batch["speech"] = speech
    return batch


# load dummy dataset and read soundfiles
ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
ds = ds.map(map_to_array)

transcript = ds['text'][0]
speech = ds["speech"][0]

Speech encoder NLP decoder

model = SpeechMixED("facebook/wav2vec2-base-960h", "facebook/bart-large")

transcript_tensor = model.tokenizer(transcript, return_tensors="pt").input_ids
speech_tensor = model.processor(speech, return_tensors="pt").input_values

model(speech_tensor, transcript_tensor)

Speech encoder NLP decoder only fine-tune on cross attention/projection/decoder embedding

model = SpeechMixED("facebook/wav2vec2-base-960h", "facebook/bart-large", ftl=True)

transcript_tensor = model.tokenizer(transcript, return_tensors="pt").input_ids
speech_tensor = model.processor(speech, return_tensors="pt").input_values

model(speech_tensor, transcript_tensor)

Speech encoder NLP encoder decoder

model = SpeechMixEED("facebook/wav2vec2-base-960h", "facebook/bart-large")

transcript_tensor = model.tokenizer(transcript, return_tensors="pt").input_ids
speech_tensor = model.processor(speech, return_tensors="pt").input_values

model(speech_tensor, transcript_tensor)

Speech encoder NLP encoder decoder only fine-tune on layer norm and attention

model = SpeechMixEED("facebook/wav2vec2-base-960h", "facebook/bart-large", lna=True)

transcript_tensor = model.tokenizer(transcript, return_tensors="pt").input_ids
speech_tensor = model.processor(speech, return_tensors="pt").input_values

model(speech_tensor, transcript_tensor)

Speech encoder NLP encoder decoder only fine-tune on speech encoder

model = SpeechMixEED("facebook/wav2vec2-base-960h", "facebook/bart-large", fne=True)

transcript_tensor = model.tokenizer(transcript, return_tensors="pt").input_ids
speech_tensor = model.processor(speech, return_tensors="pt").input_values

model(speech_tensor, transcript_tensor)

Installation

pip install

pip install speechmix

Build from source

git clone and cd into this project.

pip install -e .
Owner
Eric Lam
NLP researcher, Data scientist and computer science engineer.
Eric Lam
GitHub Repository
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch

nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank li

Tae-Hwan Jung 11.9k Jan 08, 2023
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP

Graph4NLP Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP).

Graph4AI 1.5k Dec 23, 2022
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.

UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s

Google 1.4k Dec 28, 2022
A CRM department in a local bank works on classify their lost customers with their past datas. So they want predict with these method that average loss balance and passive duration for future.

Rule-Based-Classification-in-a-Banking-Case. A CRM department in a local bank works on classify their lost customers with their past datas. So they wa

ÖMER YILDIZ 4 Mar 20, 2022
Segmenter - Transformer for Semantic Segmentation

Segmenter - Transformer for Semantic Segmentation

592 Dec 27, 2022
A cross platform OCR Library based on PaddleOCR & OnnxRuntime

A cross platform OCR Library based on PaddleOCR & OnnxRuntime

RapidOCR Team 767 Jan 09, 2023
Korea Spell Checker

한국어 문서 koSpellPy Korean Spell checker How to use Install pip install kospellpy Use from kospellpy import spell_init spell_checker = spell_init() # d

kangsukmin 2 Oct 20, 2021
Official implementation of Meta-StyleSpeech and StyleSpeech

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code

min95 169 Jan 05, 2023
Use Tensorflow2.7.0 Build OpenAI'GPT-2

TF2_GPT-2 Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型 优点 使用无监督技术 拥有大量词汇量 可实现续写（堪比“xx梦续写”） 实现对话后续将应用于FloatTech的Bot

Watermelon 9 Sep 13, 2022
PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis

PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis

YangHeng 567 Jan 07, 2023
Trains an OpenNMT PyTorch model and SentencePiece tokenizer.

Trains an OpenNMT PyTorch model and SentencePiece tokenizer. Designed for use with Argos Translate and LibreTranslate.

Argos Open Tech 61 Dec 13, 2022
基于“Seq2Seq+前缀树”的知识图谱问答

KgCLUE-bert4keras 基于“Seq2Seq+前缀树”的知识图谱问答 简介 博客：https://kexue.fm/archives/8802 环境 软件：bert4keras=0.10.8 硬件：目前的结果是用一张Titan RTX（24G）跑出来的。 运行 第一次运行的时候，会给知

苏剑林(Jianlin Su) 65 Dec 12, 2022
A Domain Specific Language (DSL) for building language patterns. These can be later compiled into spaCy patterns, pure regex, or any other format

RITA DSL This is a language, loosely based on language Apache UIMA RUTA, focused on writing manual language rules, which compiles into either spaCy co

Šarūnas Navickas 60 Sep 26, 2022
TFPNER: Exploration on the Named Entity Recognition of Token Fused with Part-of-Speech

TFPNER TFPNER: Exploration on the Named Entity Recognition of Token Fused with Part-of-Speech Named entity recognition (NER), which aims at identifyin

1 Feb 07, 2022
Python interface for converting Penn Treebank trees to Stanford Dependencies and Universal Depenencies

PyStanfordDependencies Python interface for converting Penn Treebank trees to Universal Dependencies and Stanford Dependencies. Example usage Start by

David McClosky 64 May 08, 2022
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence

Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence

9 Jan 08, 2023
This code extends the neural style transfer image processing technique to video by generating smooth transitions between several reference style images

Neural Style Transfer Transition Video Processing By Brycen Westgarth and Tristan Jogminas Description This code extends the neural style transfer ima

Brycen Westgarth 110 Jan 07, 2023
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation

SHAS: Approaching optimal Segmentation for End-to-End Speech Translation In this repo you can find the code of the Supervised Hybrid Audio Segmentatio

Machine Translation @ UPC 21 Dec 20, 2022
Simple multilingual lemmatizer for Python, especially useful for speed and efficiency

Simplemma: a simple multilingual lemmatizer for Python Purpose Lemmatization is the process of grouping together the inflected forms of a word so they

Adrien Barbaresi 70 Dec 29, 2022
A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.

GuwenModels: 古文自然语言处理模型合集, 收录互联网上的古文相关模型及资源. A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.

Ethan 66 Dec 26, 2022