82 skills found · Page 1 of 3
k2-fsa / Sherpa OnnxSpeech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages
pyannote / Pyannote AudioNeural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
philipperemy / Deep SpeakerDeep Speaker: an End-to-End Neural Speaker Embedding System.
taylorlu / Speaker Diarizationspeaker diarization by uis-rnn and speaker embedding by vgg-speaker-recognition
Jungjee / RawNetOfficial repository for RawNet, RawNet2, and RawNet3
qqueing / DeepSpeaker PytorchSpeaker embedding(verification and recognition) using Pytorch
manojpamk / Pytorch XvectorsDeep speaker embeddings in PyTorch, including x-vectors. Code used in this work: https://arxiv.org/abs/2007.16196
andabi / Voice VectorDeep neural networks for getting text-independent speaker embedding written in TensorFlow
yistLin / DvectorSpeaker embedding (d-vector) trained with GE2E loss
Walleclipse / Deep Speaker Speaker Recognition SystemKeras implementation of ‘’Deep Speaker: an End-to-End Neural Speaker Embedding System‘’ (speaker recognition)
Sharad24 / Neural Voice Cloning With Few SamplesImplementation of Neural Voice Cloning with Few Samples Research Paper by Baidu
jefflai108 / Pytorch Kaldi Neural Speaker EmbeddingsA light weight neural speaker embeddings extraction based on Kaldi and PyTorch.
hbredin / TristouNetTristouNet: Triplet Loss for Speaker Turn Embedding
HaoFengyuan / X TF GridNetThe implementation of "X-TF-GridNet: A Time-Frequency Domain Target Speaker Extraction Network with Adaptive Speaker Embedding Fusion", which is accepted by Information Fusion.
RF5 / Simple Speaker EmbeddingA speaker embedding network in Pytorch that is very quick to set up and use for whatever purposes.
Labmem-Zhouyx / CDFSE FastSpeech2The Official Implementation of “Content-Dependent Fine-Grained Speaker Embedding for Zero-Shot Speaker Adaptation in Text-to-Speech Synthesis”
liyunlongaaa / NSD MS2SCHIME-7/8 diarization champion system: neural speaker diarization using memory-aware multi-speaker embedding with sequence-to-sequence architecture
Wadaboa / TitanetSpeaker identification/verification models for Machine Learning for Computer Vision class at UNIBO
Maokui-He / NSD MA MSEA pytorch implementation of the paper "ANSD-MA-MSE: Adaptive Neural Speaker Diarization Using Memory-Aware Multi-Speaker Embedding"
kaistmm / Seed Pytorch[INTERSPEECH 2025] Official code for "SEED: Speaker Embedding Enhancement Diffusion Model"
