Taejin Park

Auto-Tuning-Spectral-Clustering. This repo is for the SPL paper "Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap"

tensorflow-vs-pytorch. Guide for both TensorFlow and PyTorch in comparative way

llm_speaker_tagging. SLT 2024 Challenge: Post-ASR-Speaker-Tagging

Python-Speaker-Diarization. Python3 code for the IEEE SPL paper "Auto-Tuning Spectral Clustering for SpeakerDiarization Using Normalized Maximum Eigengap"

music-noise-segmentation-on-a-spectrogram. MNSS (Music Noise Segmentation on a Spectrogram) is a deep-neural network based preprocessing technique that pre-filters unnecessary noise. MNSS is based on the convolutional neural networks and uses softmax value as a probability of noise existence.

prj_spkembd. Speaker embedding extractor for various tasks.

usc_cs566_project. CS566 NLP text generation project

Multiscale-Speaker-Diarization. This repository is for the paper titled "Multiscale Speaker Diarization with Neural Affinity Score Fusion

diarization_annotation. Diarization annotation files

meeteval. MeetEval - A meeting transcription evaluation toolkit