文本标注位于 metadata.csv 文件。 其中19 个转录本包含非 ASCII 字符(例如,LJ016-0257 包含“raison d'être”) 样例如下: 第一段音频 LJ001-0001 (10s): > Printing in the only sense with which we are at present concerned differs from most if not from all the arts and crafts represented in t...
[Russian] This script will split audio file on silence, transcript it with google recognition and save it in LJSpeech-1.1 dataset manner. pythongoogle-cloudspeech-to-texttranscriptorrussian-languageljspeechaudio-transcription UpdatedMar 29, 2021 ...
LJSpeech公司 3625.02M 362 浏览 0 喜欢 0 次下载 0 条讨论 Others Classification 分享 Share 收藏 Favorite 0 0 数据介绍 文件预览 相关论文 Code 分享讨论(0) 使用声明 启动Notebook开发 数据结构 ? 3625.02M * 以上分析是由系统提取分析形成的结果,具体实际数据为准。 README.md # Datas...
What should I do ? The reason for such warnings is that there is '͡' in metadata.csv in ljspeech, but '͡' is not declared in characters. If you want to remove the warning, add '͡' to the characters or punctuations in your characters_class. But if '͡' is not used a l...
The LJ Speech 喜爱 2 这是一个公共领域的语音数据集,包含来自单个演讲者的13,100个简短音频片段,这些片段来自7部非小说类书籍。 为每个剪辑提供了转录。 剪辑的长度从1到10秒不等,总长度约为24小时。 缘梦枫华 4枚 CC0 4 21 2020-11-12 详情 相关项目 评论(0) 创建项目 数据集介绍 这是一个公共领域...
This is a checkpoint for the Tacotron 2 model that was trained in NeMo on LJspeech for 1200 epochs. It was trained with Apex/Amp optimization level O0, with 8 * 16GB V100, and with a batch size of 48 per GPU for a total batch size of 384. ...
人工智能模型社区圈1个主题内容 ChatGPT注册使用圈0个主题内容 算力百科圈0个主题内容 bug及解决办法圈0个主题内容 数据集应用社区圈7个主题内容 AI大学圈2个主题内容 应用案例:双目作为3D相机,仿照人类双眼感知世界 卷积神经网络(Convolutional Neural Networks) ...
This repository provides all the necessary tools for using a HiFIGAN vocoder trained with LJSpeech. The pre-trained model takes in input a spectrogram and produces a waveform in output. Typically, a vocoder is used after a TTS model that converts an input text into a spectrogram. ...
HiFTNet: A Fast High-Quality Neural Vocoder with Harmonic-plus-Noise Filter and Inverse Short Time Fourier Transform - HiFTNet/LJSpeech-1.1/training.txt at main · yl4579/HiFTNet
from concurrent.futures import ProcessPoolExecutor from functools import partial import numpy as np import os from util import audio def build_from_path(in_dir, out_dir, num_workers=1, tqdm=lambda x: x): '''Preprocesses the LJ Speech dataset from a given input path into a given output ...