https://github.com/SoulProficiency/speechseparation-GALR
Effective Low-Cost Time-Domain Audio Separation Using Globally Attentive Locally Recurrent Networks
Papers with Code 아카이브
Speech Separation
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The task of extracting all overlapping speech sources in a given mixed speech signal refers to the Speech Separation. Speech Separation is a special scenario of source separation problem, where the focus is only on the overlapping speech signal sources and other interferences such as music or noise signals are not the main concern of the study. A recent representative Github project can be referred to ClearerVoice-Studio.
Source: A Unified Framework for Speech Separation
Image credit: Speech Separation of A Target Speaker Based on Deep Neural Networks
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/SoulProficiency/speechseparation-Sandglasset
Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
https://github.com/SsssSunhy/Tasnet-Mindspore-on-Librimix
TasNet: time-domain audio separation network for real-time, single-channel speech separation
https://github.com/ZhangYu-x/dprnn_mindspore
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation
https://github.com/Zhongyang-debug/Attention-Is-All-You-Need-In-Speech-Separation
https://github.com/Zhongyang-debug/Effective-Low-Cost-Time-Domain-Audio-Separation-Using-Globally-Attentive-Locally-Recurrent-Networks
Effective Low-Cost Time-Domain Audio Separation Using Globally Attentive Locally Recurrent Networks
https://github.com/Zhongyang-debug/Sandglasset-A-Light-Multi-Granularity-Self-Attentive-Network-For-Time-Domain-Speech-Separation
Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
https://github.com/abugler/SMLFinalProject
Deep clustering: Discriminative embeddings for segmentation and separation
https://github.com/adamwhitakerwilson/speaker_separation
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/alibabasglab/frcrn
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/alibabasglab/mossformer
https://github.com/anton-jeran/FAST-RIR
MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes
https://github.com/areffarhadi/mamba-asr
https://github.com/bill9800/speech_separation
Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
https://github.com/e13000/directional_sparse_filtering
https://github.com/enk100/speaker_separation
Voice Separation with an Unknown Number of Multiple Speakers
https://github.com/etzinis/unsup_speech_enh_adaptation
Sudo rm -rf: Efficient Networks for Universal Audio Source Separation
https://github.com/facebookresearch/demucs
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/facebookresearch/visualvoice
VisualVoice: Audio-Visual Speech Separation with Cross-Modal Consistency
https://github.com/fchest/uPIT
https://github.com/fgnt/mms_msg
Deep clustering: Discriminative embeddings for segmentation and separation
https://github.com/fgnt/padertorch
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation
https://github.com/funcwj/conv-tas-net
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/funcwj/conv-tasnet
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/ishandutta2007/Speech-Denoising-Landscape
Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network
https://github.com/jack20951948/Deep-Clustering
Deep clustering: Discriminative embeddings for segmentation and separation
https://github.com/jusperlee/librispace
SonicSim: A customizable simulation platform for speech processing in moving sound source scenarios
https://github.com/jyhan03/channel-decorrelation
Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
https://github.com/jzi040941/MISOnet
Multi-microphone Complex Spectral Mapping for Utterance-wise and Continuous Speech Separation
https://github.com/kaituoxu/Conv-TasNet
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/kaituoxu/TasNet
TasNet: time-domain audio separation network for real-time, single-channel speech separation
https://github.com/khfs/DuplexMamba
https://github.com/lordet01/deep_clustering
Deep clustering: Discriminative embeddings for segmentation and separation
https://github.com/lyqcom/dprnn
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation
https://github.com/magnumresearchgroup/auxiliaryrawnet
Complementing Handcrafted Features with Raw Waveform Using a Light-weight Auxiliary Model
https://github.com/meokz/looking-to-listen
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.