hnbrh

hnbrh's Stars

• Idlak/Living-Audio-Dataset

  A "Crowd-Built" continuously growing speech dataset with transcripts. The dataset contains multiple languages and is intended for anyone to be able to add to it.

  Language:Python4110

• hirofumi0810/asr_preprocessing

  Python implementation of pre-processing for End-to-End speech recognition

  Language:Python6923

• Edresson/TTS-Portuguese-Corpus

  Open Source Text-To-Speech Portuguese Dataset

  15517

• gheyret/UQSpeechDataset

  Uyghur Single Speaker Speech Dataset. ウイグル語音声データセット

  217

• hnbrh/Speech-Command-Recognition-with-Capsule-Network

  Speech command recognition with capsule network & various NNs / KWS on Google Speech Command Dataset.

  1

• vj-1988/AudioNet-V1

  1D CNN based classifier for Speech Commands Dataset

  Language:Python85

• okkyibrohim/id-multi-label-hate-speech-and-abusive-language-detection

  The Dataset for Multi Label Hate Speech and Abusive Language Detection in Indonesian Twitter

  Language:TeX6128

• cyrta/awesome-speech-enhancement

  A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.

  6015

• ialfina/id-hatespeech-detection

  The Dataset for Hate Speech Detection in Indonesian (Bahasa Indonesia)

  2617

• kakaobrain/jejueo

  Jejueo Datasets for Machine Translation and Speech Synthesis

  Language:Python758

• jupiter126/Create_Speech_Dataset

  Creates a speech dataset for deep learning

  Language:Shell91

• ainy/shershe

  Speech recognition dataset based on russian audiobook, sentance-level split

  Language:Python181

• akhil2495/multi-modal-emotion-recognition

  A repository for emotion recognition from speech, text and mocap data from IEMOCAP dataset

  Language:Jupyter Notebook124

• codersinthestorm/RecurrentNN_SpeechRecognition

  A model based in Tensorflow to recognize words from the 30 word Speech Commands Dataset from Google using LSTM based Recurrent Neural Network.

  Language:Python103

• aymeam/Datasets-for-Hate-Speech-Detection

  Datasets for Hate Speech Detection

  11411

• hnbrh/VERBO-emotional-speech-dataset

  VERBO (Voice Emotion Recognition dataBase in pOrtuguese language)

  1

• hnbrh/GenderClassifierLibriSpeech

  Gender Classification of the speaker from LibriSpeech Dataset

  1

• gionanide/Speech_Signal_Processing_and_Classification

  Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

  Language:Python23863

• Demfier/multimodal-speech-emotion-recognition

  Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)

  Language:Jupyter Notebook39684

• mravanelli/pySpeechRev

  This python code performs an efficient speech reverberation starting from a dataset of close-talking speech signals and a collection of acoustic impulse responses.

  Language:Python9325

• klintan/swedish-asr-dataset

  Jupyter Notebooks for creating Speech datasets

  Language:Jupyter Notebook4612

• Kyubyong/css10

  CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages

  Language:HTML45760

• festvox/datasets-CMU_Wilderness

  CMU Wilderness Multilingual Speech Dataset

  Language:Shell27249

• Vicomtech/hate-speech-dataset

  Hate speech dataset from Stormfront forum manually labelled at sentence level.

  16257

• t-davidson/hate-speech-and-offensive-language

  Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017

  Language:Jupyter Notebook784326

• x4nth055/emotion-recognition-using-speech

  Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

  Language:Python572229