YQ (@ranchlai)
github

ranchlai

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  • Stars
    star
    720
  • Global Rank 41,791 (Top 2 %)
  • Followers 80
  • Following 25
  • Registered over 11 years ago
  • Most used languages
    Python
         85.7 %
    Jupyter Notebook
         14.3 %
  • Location 🇨🇳 China
  • Country Total Rank 7,086
  • Country Ranking
    Jupyter Notebook
         801
    Python
         1,195

Top repositories

1

mandarin-tts

Chinese Mandarin tts text-to-speech 中文 (普通话) 语音 合成 , by fastspeech 2 , implemented in pytorch, using waveglow as vocoder, with biaobei and aishell3 datasets
Python
462
star
2

speaker-verification

Speaker verification using ResnetSE (EER=0.0093) and ECAPA-TDNN
Python
88
star
3

awesome-speaker-embedding

A curated list of speaker-embedding speaker-verification, speaker-identification resources.
44
star
4

lectures

B站视频课程配套资料
Jupyter Notebook
37
star
5

pinyin2hanzi

拼音转汉字, convert pinyin to 汉字 using deep networks
Python
22
star
6

nlpcc2023-shared-task-diaASQ

NLPCC2023 shared-task DiaASQ first-place solution. （NLPCC2023对话式细粒度情感识别大赛第一名方案）
Python
10
star
7

adversarial_example

transform sky to cat
Jupyter Notebook
7
star
8

clip.paddle

OpenAI clip implementation in PaddlePaddle
Python
5
star
9

sound_classification

pretrained sound classification models on esc-50. acc=0.937
Python
3
star
10

wav2vec-2.0

Wav2vec2 English speech recognition in PaddlePaddle
Python
3
star
11

speaker-benchmarks

Testing SOTA open-source Voxceleb speaker models on Aishell-3
Python
2
star
12

quantizations

A collection of quantization recipes for various large models including Llama-2-70B, QWen-14B, Baichuan-2-13B, and more.
Python
2
star
13

preprocessing

Audio preprocessing using PaddleAudio
Python
1
star
14

dcase2021_task1b

Python
1
star
15

gsm8k

gsm8k in json format
Python
1
star
16

Awesome-generative-recommendation-using-llm

This repository contains a collection of papers, blog posts, and tutorials on generative recommendation using large language models
1
star
17

awesome-sound

Awesome acoustic(sound) scenes and events classification and detection, papers, code, toolkits, frameworks and libraries
1
star