Python SDK for working with Voicegain Speech-to-Text

Overview

Voicegain Speech-to-Text Python SDK

Python SDK for the Voicegain Speech-to-Text API.

This API allows for large vocabulary speech-to-text transcription as well as grammar-based speech recognition. Both real-time and offline use cases are supported.

You can see the core Voicegain API documentation here.

The complete documentation for the API covered by this SDK is available here - this link requires an account on the Voicegain portal - see below for how to sign up.

Requirements

In order to use this API you need account with Voicegain. You can create an account by signing up on Voicegain Portal. No credit card required to sign up.

You can see pricing here - basically, it is 1 cent a minute for off-line and 1.25 cents a minute for real-time. There is a Free Tier of 600 minutes that renews each month.

Installation

From PyPI directly:

pip install voicegain-speech

Examples

  • sync_transcribe example:

configuration:

" configuration = Configuration() configuration.access_token = JWT api_client = ApiClient(configuration=configuration) ">
from voicegain_speech import ApiClient
from voicegain_speech import Configuration
from voicegain_speech import TranscribeApi
import base64


# configure your JWT token
JWT = "Your 
   
    "
   

configuration = Configuration()
configuration.access_token = JWT

api_client = ApiClient(configuration=configuration)

transcribe local file:

transcribe_api = TranscribeApi(api_client)
file_path = "Your local file path"

with open(file_path, "rb") as f:
    audio_base64 = base64.b64encode(f.read()).decode()

response = transcribe_api.asr_transcribe_post(
    sync_transcription_request={
        "audio": {
            "source": {
                "inline": {
                    "data": audio_base64
                }
            }
        }
    }
)

alternatives = response.result.alternatives
if alternatives:
    local_result = alternatives[0].utterance
    print("result from file: ", local_result)

else:
    local_result = None
    print("no transcription")

More examples can be found in examples folder on our GitHub


Learn more about Voicegain Platform at www.voicegain.ai

You might also like...
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
Speech Recognition for Uyghur using Speech transformer

Speech Recognition for Uyghur using Speech transformer Training: this model using CTC loss and Cross Entropy loss for training. Download pretrained mo

Text-Summarization-using-NLP - Text Summarization using NLP  to fetch BBC News Article and summarize its text and also it includes custom article Summarization Text to speech converter with GUI made in Python.
Text to speech converter with GUI made in Python.

Text-to-speech-with-GUI Text to speech converter with GUI made in Python. To run this download the zip file and run the main file or clone this repo.

A relatively simple python program to generate one of those reddit text to speech videos dominating youtube.

Reddit text to speech generator A basic reddit tts video generator Current functionality Generate videos for subs based on comments,(askreddit) so rea

This is a really simple text-to-speech app made with python and tkinter.
This is a really simple text-to-speech app made with python and tkinter.

Tkinter Text-to-Speech App by Souvik Roy This is a really simple tkinter app which converts the text you have entered into a speech. It is created wit

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril

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

Releases(1.73.0)
Owner
Voicegain
Speech-to-Text Platform - Cloud and Edge
Voicegain
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.09

Keon Lee 142 Jan 06, 2023
Chinese Named Entity Recognization (BiLSTM with PyTorch)

BiLSTM-CRF for Name Entity Recognition PyTorch version A PyTorch implemention of Bi-LSTM-CRF model for Chinese Named Entity Recognition. 使用 PyTorch 实现

5 Jun 01, 2022
text to speech toolkit. 好用的中文语音合成工具箱,包含语音编码器、语音合成器、声码器和可视化模块。

ttskit Text To Speech Toolkit: 语音合成工具箱。 安装 pip install -U ttskit 注意 可能需另外安装的依赖包:torch,版本要求torch=1.6.0,=1.7.1,根据自己的实际环境安装合适cuda或cpu版本的torch。 ttskit的

KDD 483 Jan 04, 2023
Japanese Long-Unit-Word Tokenizer with RemBertTokenizerFast of Transformers

Japanese-LUW-Tokenizer Japanese Long-Unit-Word (国語研長単位) Tokenizer for Transformers based on 青空文庫 Basic Usage from transformers import RemBertToken

Koichi Yasuoka 3 Dec 22, 2021
Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer

ConSERT Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer Requirements torch==1.6.0

Yan Yuanmeng 478 Dec 25, 2022
Protein Language Model

ProteinLM We pretrain protein language model based on Megatron-LM framework, and then evaluate the pretrained model results on TAPE (Tasks Assessing P

THUDM 77 Dec 27, 2022
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect

Intel Labs 2.9k Jan 02, 2023
A look-ahead multi-entity Transformer for modeling coordinated agents.

baller2vec++ This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling

Michael A. Alcorn 30 Dec 16, 2022
Adversarial Examples for Extreme Multilabel Text Classification

Adversarial Examples for Extreme Multilabel Text Classification The code is adapted from the source codes of BERT-ATTACK [1], APLC_XLNet [2], and Atte

1 May 14, 2022
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation

LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transform

Bytedance Inc. 2.5k Jan 03, 2023
A tool helps build a talk preview image by combining the given background image and talk event description

talk-preview-img-builder A tool helps build a talk preview image by combining the given background image and talk event description Installation and U

PyCon Taiwan 4 Aug 20, 2022
Non-Autoregressive Predictive Coding

Non-Autoregressive Predictive Coding This repository contains the implementation of Non-Autoregressive Predictive Coding (NPC) as described in the pre

Alexander H. Liu 43 Nov 15, 2022
Collection of scripts to pinpoint obfuscated code

Obfuscation Detection (v1.0) Author: Tim Blazytko Automatically detect control-flow flattening and other state machines Description: Scripts and binar

Tim Blazytko 230 Nov 26, 2022
Natural language Understanding Toolkit

Natural language Understanding Toolkit TOC Requirements Installation Documentation CLSCL NER References Requirements To install nut you need: Python 2

Peter Prettenhofer 119 Oct 08, 2022
ThinkTwice: A Two-Stage Method for Long-Text Machine Reading Comprehension

ThinkTwice ThinkTwice is a retriever-reader architecture for solving long-text machine reading comprehension. It is based on the paper: ThinkTwice: A

Walle 4 Aug 06, 2021
My Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow

Easy Data Augmentation Implementation This repository contains my Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Per

Aflah 9 Oct 31, 2022
An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI, torch2trt to accelerate. our model support for int8, dynamic input and profiling. (Nvidia-Alibaba-TensoRT-hackathon2021)

Ultra_Fast_Lane_Detection_TensorRT An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI to accelerate. our model support for in

steven.yan 121 Dec 27, 2022
Exploration of BERT-based models on twitter sentiment classifications

twitter-sentiment-analysis Explore the relationship between twitter sentiment of Tesla and its stock price/return. Explore the effect of different BER

Sammy Cui 2 Oct 02, 2022
L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources.

L3Cube-MahaCorpus L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual

21 Dec 17, 2022
☀️ Measuring the accuracy of BBC weather forecasts in Honolulu, USA

Accuracy of BBC Weather forecasts for Honolulu This repository records the forecasts made by BBC Weather for the city of Honolulu, USA. Essentially, t

Max Halford 12 Oct 15, 2022