pipeline(管道)是huggingface transformers库中一种极简方式使用大模型推理的抽象,将所有大模型分为音频(Audio)、计算机视觉(Computer vision)、自然语言处理(NLP)、多模态(Multimodal)等4大类,28小类任务(tasks),共计覆盖32万个模型。 今天介绍Audio音频的第二篇,自动语音识别(automatic-speech-recognition),在huggingface...
简介: 【人工智能】Transformers之Pipeline(二):自动语音识别(automatic-speech-recognition) 一、引言 pipeline(管道)是huggingface transformers库中一种极简方式使用大模型推理的抽象,将所有大模型分为音频(Audio)、计算机视觉(Computer vision)、自然语言处理(NLP)、多模态(Multimodal)等4大类,28小类任务(tasks),共...
ModuleNotFoundError: AutomaticSpeechRecognitionPipeline: No module named ‘funasr’ 一、前言 跑阿里语音AI模搭的语音识别遇到问题: ModuleNotFoundError: No module named ‘funasr’ During handling of the above exception, another exception occurred: Traceback (most recent call last): File “test_asr.p...
TypeError: AutomaticSpeechRecognitionPipeline.__init__() missing 1 required positional argument: 'feature_extractor' Traceback: File "C:\Users\gadel\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\streamlit\runtime\scriptrunner\...
CVPR 2020 An Effective Pipeline for a Real world Clothes Retrieval System 28 -- 16:08 App Lecture 5.2 — Octave Tutorial || Moving Data Around — [ Machine Learning | An 23 -- 8:54 App RNN W3L09 : Speech Recognition 103 -- 19:38 App (seventh RacketCon): Charles Earl: Deep Learni...
In the paper, we present a software pipeline for speech recognition to automate the creation of training datasets, based on desired unlabeled audios, for low resource languages and domain-specific area. Considering the commoditizing of speech recognition, more teams build domain-specific models as...
Figure 1. Deep learning speech recognition pipeline Datasets are essential in any deep learning application. Neural networks function similarly to the human brain. The more data you use to teach the model, the more it learns. The same is true for the speech recognition pipeline. A few popular...
My own practices prove that fifoqueue input pipeline would improve the training speed in some time. If you want to look the history of speech recognition, I have collected the significant papers since 1981 in the ASR field. You can read awesome paper list in my repo awesome-speech-...
Traditional speech recognition takes a generative approach, modeling the full pipeline of how speech sounds are produced in order to evaluate a speech sample. We would start from a language model that encapsulates the most likely orderings of words that are generated (e.g. an n-gram model), ...
Google Summer of Code 2018 Project: Automatic Speech Recognition for Speech-to-Text on Chinese - CynthiaSuwi/ASR-for-Chinese-Pipeline