speech-emotion-recognition

Open-source SenseVoiceSmall model for Mandarin, Cantonese, English, Japanese, and Korean ASR, language ID, emotion recognition, and audio event detection.

💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

The code for our INTERSPEECH 2020 paper - Jointly Fine-Tuning "BERT-like'" Self Supervised Models to Improve Multimodal Speech Emotion Recognition

Callytics is an advanced call analytics solution that leverages speech recognition and large language models (LLMs) technologies to analyze phone conversations from customer service and call centers.

An implementation of Speech Emotion Recognition, based on HuBERT model, training with PyTorch and HuggingFace framework, and fine-tuning on the RAVDESS dataset.

Awesome Speech Dataset, including download links and a brief explanation for each resource. These datasets provide diverse and high-quality speech data covering various domains such as conversational, academic, political, and more.

A multimodal SER project combining BERT and ECAPA-TDNN with cross-attention-based fusion on the IEMOCAP dataset.