easySpeech is an open-source Python wrapper for google speech to text API that doesn't require PyAudio(So you especially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers

Overview

easySpeech


GitHub issues GitHub forks GitHub stars GitHub license GitHub last commit GitHub contributors Downloads


easySpeech is an open source python wrapper for google speech to text api that doesn't require PyAaudio(So you specially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers

Installation

You can install easySpeech very easily using the following command

pip3 install easySpeech

Usage

  • Using google speech to text api
    By default easySpeech comes with a default api key which you can for testing purposes using the following code.
from easySpeech import speech
a=speech.speech('google')
print(a)

For production purpose use your own key because google can revoke the default api key at any time. Get your own api key from http://www.chromium.org/developers/how-tos/api-keys and use the following code

from easySpeech import speech
a=speech.speech('google',key="your api key")
print(a)

Specifying the duration of speech recognition in seconds(default value is 5 seconds)

from easySpeech import speech
a=speech.speech('google',duration = 10)
print(a)

Specifying the sample frequency(default is 44100)

from easySpeech import speech
a=speech.speech('google',duration = 10,freq = 44100)
print(a)

Specifying the language(works only for google speech api and default is english)

from easySpeech import speech
a=speech.speech('google',language="en-US")
print(a)

Converting an audio file to text(Currently it supports only wav file)

from easySpeech import speech
a=speech.google_audio('recording.wav')
print(a)
  • Using hugging face transformers(works offline and no need of any kind of api key) For using easySpeech with hugging face transformers use the following code.
from easySpeech import speech
a=speech.speech('ml')
print(a)

Specifying the duration of speech recognition in seconds(default valus is 5 seconds)

from easySpeech import speech
a=speech.speech('ml',duration = 10)
print(a)

Specifying the sample frequency(default is 44100)

from easySpeech import speech
a=speech.speech('ml',duration = 10,freq = 44100)
print(a)

Converting an audio file to text(Currently it supports only wav file)

from easySpeech import ml
a=ml.ml('recording.wav')
print(a)
  • Recording audio
    For recording audio use the following code
from easySpeech import speech
speech.recorder('recording.wav')

For recording audio with a specific frequency use the following code(default is 44100)

from easySpeech import speech
speech.recorder('recording.wav',freq = 50000)

For recording audio for a specific duration use the following code(default is 5s)

from easySpeech import speech
speech.recorder('recording.wav',duration = 50)

How to contribute

Since it is a free software , you can contribute to make it better. New contributors are always welcome, whether you write code, create resources, report bugs, or suggest features.

The easySpeech is written primarily in Python3x

Have a look at the open issues to find a mission that resonates with you.


Contact

Email: [email protected]
If you find any bug make a issue immediately.

License

easySpeech is lisenced under MIT license

MIT License | Copyright (c) 2021 SaptakBhoumik

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software
You might also like...
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.

Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.

A Python module made to simplify the usage of Text To Speech and Speech Recognition.
A Python module made to simplify the usage of Text To Speech and Speech Recognition.

Nav Module The solution for voice related stuff in Python Nav is a Python module which simplifies voice related stuff in Python. Just import the Modul

A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code or write code yourself
A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code or write code yourself

Scriptfab - What is it? A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code

A Python wrapper for simple offline real-time dictation (speech-to-text) and speaker-recognition using Vosk.

Simple-Vosk A Python wrapper for simple offline real-time dictation (speech-to-text) and speaker-recognition using Vosk. Check out the official Vosk G

PocketSphinx is a lightweight speech recognition engine, specifically tuned for handheld and mobile devices, though it works equally well on the desktop

PocketSphinx 5prealpha This is PocketSphinx, one of Carnegie Mellon University's open source large vocabulary, speaker-independent continuous speech r

Code for ACL 2022 main conference paper "STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation".

STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST

Creating an Audiobook (mp3 file) using a Ebook (epub) using BeautifulSoup and Google Text to Speech

epub2audiobook Creating an Audiobook (mp3 file) using a Ebook (epub) using BeautifulSoup and Google Text to Speech Input examples qual a pasta do seu

Command Line Text-To-Speech using Google TTS
Command Line Text-To-Speech using Google TTS

cli-tts Thanks to gTTS by @pndurette! This is an interactive command line text-to-speech tool using Google TTS. Just type text and the voice will be p

Releases(v1.0.2)
  • v1.0.2(Jun 3, 2021)

    easySpeech is an open-source Python wrapper for google speech to text API that doesn't require PyAudio(So you especially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers. You can also use it to record sound. What's new

    1. It is now even more easy to use
    2. Minor bug fix
    Source code(tar.gz)
    Source code(zip)
  • v1.0.1(Jun 1, 2021)

    easySpeech is an open-source Python wrapper for google speech to text API that doesn't require PyAudio(So you especially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers. You can also use it to record sound.

    Source code(tar.gz)
    Source code(zip)
pkuseg多领域中文分词工具; The pkuseg toolkit for multi-domain Chinese word segmentation

pkuseg:一个多领域中文分词工具包 (English Version) pkuseg 是基于论文[Luo et. al, 2019]的工具包。其简单易用,支持细分领域分词,有效提升了分词准确度。 目录 主要亮点 编译和安装 各类分词工具包的性能对比 使用方式 论文引用 作者 常见问题及解答 主要

LancoPKU 6k Dec 29, 2022
Paddle2.x version AI-Writer

Paddle2.x 版本AI-Writer 用魔改 GPT 生成网文。Tuned GPT for novel generation.

yujun 74 Jan 04, 2023
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents

BROS (BERT Relying On Spatiality) is a pre-trained language model focusing on text and layout for better key information extraction from documents. Given the OCR results of the document image, which

Clova AI Research 94 Dec 30, 2022
Topic Modelling for Humans

gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ

RARE Technologies 13.8k Jan 02, 2023
Smart discord chatbot integrated with Dialogflow to manage different classrooms and assist in teaching!

smart-school-chatbot Smart discord chatbot integrated with Dialogflow to interact with students naturally and manage different classes in a school. De

Tom Huynh 5 Oct 24, 2022
Entity Disambiguation as text extraction (ACL 2022)

ExtEnD: Extractive Entity Disambiguation This repository contains the code of ExtEnD: Extractive Entity Disambiguation, a novel approach to Entity Dis

Sapienza NLP group 121 Jan 03, 2023
Exploring dimension-reduced embeddings

sleepwalk Exploring dimension-reduced embeddings This is the code repository. See here for the Sleepwalk web page. License and disclaimer This program

S. Anders's research group at ZMBH 91 Nov 29, 2022
SimCTG - A Contrastive Framework for Neural Text Generation

A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,

Yixuan Su 345 Jan 03, 2023
ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab

AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode

Alibaba 1.4k Jan 04, 2023
📝An easy-to-use package to restore punctuation of the text.

✏️ rpunct - Restore Punctuation This repo contains code for Punctuation restoration. This package is intended for direct use as a punctuation restorat

Daulet Nurmanbetov 72 Dec 30, 2022
Live Speech Portraits: Real-Time Photorealistic Talking-Head Animation (SIGGRAPH Asia 2021)

Live Speech Portraits: Real-Time Photorealistic Talking-Head Animation This repository contains the implementation of the following paper: Live Speech

OldSix 575 Dec 31, 2022
Fine-tuning scripts for evaluating transformer-based models on KLEJ benchmark.

The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und

Allegro Tech 17 Oct 18, 2022
a test times augmentation toolkit based on paddle2.0.

Patta Image Test Time Augmentation with Paddle2.0! Input | # input batch of images / / /|\ \ \ # apply

AgentMaker 110 Dec 03, 2022
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoenc

Venelin Valkov 1.8k Dec 31, 2022
Pretrained Japanese BERT models

Pretrained Japanese BERT models This is a repository of pretrained Japanese BERT models. The models are available in Transformers by Hugging Face. Mod

Inui Laboratory 387 Dec 30, 2022
Nested Named Entity Recognition for Chinese Biomedical Text

CBio-NAMER CBioNAMER (Nested nAMed Entity Recognition for Chinese Biomedical Text) is our method used in CBLUE (Chinese Biomedical Language Understand

8 Dec 25, 2022
Guide to using pre-trained large language models of source code

Large Models of Source Code I occasionally train and publicly release large neural language models on programs, including PolyCoder. Here, I describe

Vincent Hellendoorn 947 Dec 28, 2022
A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP

A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP

420 Dec 28, 2022
LV-BERT: Exploiting Layer Variety for BERT (Findings of ACL 2021)

LV-BERT Introduction In this repo, we introduce LV-BERT by exploiting layer variety for BERT. For detailed description and experimental results, pleas

Weihao Yu 14 Aug 24, 2022
KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark.

KLUE Baseline Korean(한국어) KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark. See our paper fo

74 Dec 13, 2022