init

experiment_cache/cluster/w2v_bert_se.expresso.speaker_id.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5a7b8722c152981c4e514dfaf90eb17dbefbc653dbee44c59bee558aa2a9cb52
-size 162416

experiment_cache/cluster/w2v_bert_se.expresso.style.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:201cafca59ca308d8882d3434dd2637fe49a0c5b11b6cb8bccec7396bfc170be
-size 181626

experiment_cache/cluster/w2v_bert_se.voxceleb1-test-split.speaker_id.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d0a9a82594fdef76a933e5a21534a8af37487f7ec1b6b2e4662be6950c52ce76
-size 123308

experiment_cache/embeddings/w2v_bert_se.expresso.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6adea5c716277b2525cf78b38234da223ff9af3722635aeae19ac26e78226ef5
-size 268823097

experiment_cache/embeddings/w2v_bert_se.voxceleb1-test-split.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:03324e439f856b30e136b3b13fe9d841919b792aeaca8a6f7d65787977dca1dc
-size 112682448

experiment_cache/tsne/w2v_bert_se.expresso.speaker_id.npy

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e186ef5932df77876df41323523fdef80e17d9ae2db2e1f6452a66cd5c4d0a61
-size 93048

experiment_cache/tsne/w2v_bert_se.expresso.style.npy

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:600c2be510bb6044ab2d38a87a88ac64224d832f622b0bc8647e5c07ff2c03de
-size 93048

experiment_cache/tsne/w2v_bert_se.voxceleb1-test-split.speaker_id.npy

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5d09ce160684b68806d052b6c699819e41410df0a47fe5f1bb51bb4039b1d9c6
-size 39120

experiment_speaker_verification.py

@@ -16,10 +16,11 @@ from datasets import load_dataset
 
 from model_meta_voice import MetaVoiceEmbedding
 from model_pyannote_embedding import PyannoteEmbedding
-from model_w2v_bert import W2VBERTEmbedding
 from model_clap import CLAPEmbedding, CLAPGeneralEmbedding
-from model_xls import Wav2VecEmbedding, XLSR300MEmbedding, XLSR1BEmbedding, XLSR2BEmbedding
-from model_hubert import HuBERTBaseEmbedding, HuBERTLargeEmbedding, HuBERTXLEmbedding
+from model_speaker_embedding import (
+    W2VBERTEmbedding, Wav2VecEmbedding, XLSR300MEmbedding, XLSR1BEmbedding, XLSR2BEmbedding,
+    HuBERTBaseEmbedding, HuBERTLargeEmbedding, HuBERTXLEmbedding
+)
 
 
 def get_embedding(model_class, model_name: str, dataset_name: str, data_split: str):
@@ -118,68 +119,68 @@ def analyze_embedding(model_name: str, dataset_name: str, n_shot: int = 5, n_cro
 if __name__ == '__main__':
     # get_embedding(MetaVoiceEmbedding, "meta_voice_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(PyannoteEmbedding, "pyannote_se", "asahi417/voxceleb1-test-split", "test")
-    # get_embedding(W2VBERTEmbedding, "w2v_bert_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(CLAPEmbedding, "clap_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(CLAPGeneralEmbedding, "clap_general_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(HuBERTBaseEmbedding, "hubert_base_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(HuBERTLargeEmbedding, "hubert_large_se", "asahi417/voxceleb1-test-split", "test")
     # get_embedding(HuBERTXLEmbedding, "hubert_xl_se", "asahi417/voxceleb1-test-split", "test")
-    get_embedding(Wav2VecEmbedding, "wav2vec_se", "asahi417/voxceleb1-test-split", "test")
-    get_embedding(XLSR300MEmbedding, "xlsr_300m_se", "asahi417/voxceleb1-test-split", "test")
-    get_embedding(XLSR1BEmbedding, "xlsr_1b_se", "asahi417/voxceleb1-test-split", "test")
-    get_embedding(XLSR2BEmbedding, "xlsr_2b_se", "asahi417/voxceleb1-test-split", "test")
+    get_embedding(W2VBERTEmbedding, "w2v_bert_se", "asahi417/voxceleb1-test-split", "test")
+    # get_embedding(Wav2VecEmbedding, "wav2vec_se", "asahi417/voxceleb1-test-split", "test")
+    # get_embedding(XLSR300MEmbedding, "xlsr_300m_se", "asahi417/voxceleb1-test-split", "test")
+    # get_embedding(XLSR1BEmbedding, "xlsr_1b_se", "asahi417/voxceleb1-test-split", "test")
+    # get_embedding(XLSR2BEmbedding, "xlsr_2b_se", "asahi417/voxceleb1-test-split", "test")
 
     # get_embedding(MetaVoiceEmbedding, "meta_voice_se", "ylacombe/expresso", "train")
     # get_embedding(PyannoteEmbedding, "pyannote_se", "ylacombe/expresso", "train")
-    # get_embedding(W2VBERTEmbedding, "w2v_bert_se", "ylacombe/expresso", "train")
     # get_embedding(CLAPEmbedding, "clap_se", "ylacombe/expresso", "train")
     # get_embedding(CLAPGeneralEmbedding, "clap_general_se", "ylacombe/expresso", "train")
     # get_embedding(HuBERTBaseEmbedding, "hubert_base_se", "ylacombe/expresso", "train")
     # get_embedding(HuBERTLargeEmbedding, "hubert_large_se", "ylacombe/expresso", "train")
     # get_embedding(HuBERTXLEmbedding, "hubert_xl_se", "ylacombe/expresso", "train")
-    get_embedding(Wav2VecEmbedding, "wav2vec_se", "ylacombe/expresso", "train")
-    get_embedding(XLSR300MEmbedding, "xlsr_300m_se", "ylacombe/expresso", "train")
-    get_embedding(XLSR1BEmbedding, "xlsr_1b_se", "ylacombe/expresso", "train")
-    get_embedding(XLSR2BEmbedding, "xlsr_2b_se", "ylacombe/expresso", "train")
+    get_embedding(W2VBERTEmbedding, "w2v_bert_se", "ylacombe/expresso", "train")
+    # get_embedding(Wav2VecEmbedding, "wav2vec_se", "ylacombe/expresso", "train")
+    # get_embedding(XLSR300MEmbedding, "xlsr_300m_se", "ylacombe/expresso", "train")
+    # get_embedding(XLSR1BEmbedding, "xlsr_1b_se", "ylacombe/expresso", "train")
+    # get_embedding(XLSR2BEmbedding, "xlsr_2b_se", "ylacombe/expresso", "train")
 
     # cluster_embedding("meta_voice_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("pyannote_se", "asahi417/voxceleb1-test-split", "speaker_id")
-    # cluster_embedding("w2v_bert_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("clap_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("clap_general_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("hubert_base_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("hubert_large_se", "asahi417/voxceleb1-test-split", "speaker_id")
     # cluster_embedding("hubert_xl_se", "asahi417/voxceleb1-test-split", "speaker_id")
-    cluster_embedding("wav2vec_se", "asahi417/voxceleb1-test-split", "speaker_id")
-    cluster_embedding("xlsr_300m_se", "asahi417/voxceleb1-test-split", "speaker_id")
-    cluster_embedding("xlsr_1b_se", "asahi417/voxceleb1-test-split", "speaker_id")
-    cluster_embedding("xlsr_2b_se", "asahi417/voxceleb1-test-split", "speaker_id")
+    cluster_embedding("w2v_bert_se", "asahi417/voxceleb1-test-split", "speaker_id")
+    # cluster_embedding("wav2vec_se", "asahi417/voxceleb1-test-split", "speaker_id")
+    # cluster_embedding("xlsr_300m_se", "asahi417/voxceleb1-test-split", "speaker_id")
+    # cluster_embedding("xlsr_1b_se", "asahi417/voxceleb1-test-split", "speaker_id")
+    # cluster_embedding("xlsr_2b_se", "asahi417/voxceleb1-test-split", "speaker_id")
 
     # cluster_embedding("meta_voice_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("pyannote_se", "ylacombe/expresso", "speaker_id")
-    # cluster_embedding("w2v_bert_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("clap_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("clap_general_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("hubert_base_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("hubert_large_se", "ylacombe/expresso", "speaker_id")
     # cluster_embedding("hubert_xl_se", "ylacombe/expresso", "speaker_id")
-    cluster_embedding("wav2vec_se", "ylacombe/expresso", "speaker_id")
-    cluster_embedding("xlsr_300m_se", "ylacombe/expresso", "speaker_id")
-    cluster_embedding("xlsr_1b_se", "ylacombe/expresso", "speaker_id")
-    cluster_embedding("xlsr_2b_se", "ylacombe/expresso", "speaker_id")
+    cluster_embedding("w2v_bert_se", "ylacombe/expresso", "speaker_id")
+    # cluster_embedding("wav2vec_se", "ylacombe/expresso", "speaker_id")
+    # cluster_embedding("xlsr_300m_se", "ylacombe/expresso", "speaker_id")
+    # cluster_embedding("xlsr_1b_se", "ylacombe/expresso", "speaker_id")
+    # cluster_embedding("xlsr_2b_se", "ylacombe/expresso", "speaker_id")
 
     # cluster_embedding("meta_voice_se", "ylacombe/expresso", "style")
     # cluster_embedding("pyannote_se", "ylacombe/expresso", "style")
-    # cluster_embedding("w2v_bert_se", "ylacombe/expresso", "style")
     # cluster_embedding("clap_se", "ylacombe/expresso", "style")
     # cluster_embedding("clap_general_se", "ylacombe/expresso", "style")
     # cluster_embedding("hubert_base_se", "ylacombe/expresso", "style")
     # cluster_embedding("hubert_large_se", "ylacombe/expresso", "style")
     # cluster_embedding("hubert_xl_se", "ylacombe/expresso", "style")
-    cluster_embedding("wav2vec_se", "ylacombe/expresso", "style")
-    cluster_embedding("xlsr_300m_se", "ylacombe/expresso", "style")
-    cluster_embedding("xlsr_1b_se", "ylacombe/expresso", "style")
-    cluster_embedding("xlsr_2b_se", "ylacombe/expresso", "style")
+    cluster_embedding("w2v_bert_se", "ylacombe/expresso", "style")
+    # cluster_embedding("wav2vec_se", "ylacombe/expresso", "style")
+    # cluster_embedding("xlsr_300m_se", "ylacombe/expresso", "style")
+    # cluster_embedding("xlsr_1b_se", "ylacombe/expresso", "style")
+    # cluster_embedding("xlsr_2b_se", "ylacombe/expresso", "style")
 
 
 

model_speaker_embedding.py

@@ -1,7 +1,4 @@
-"""Meta's w2vBERT based speaker embedding.
-- feature dimension: 1024
-- source: https://huggingface.co/facebook/w2v-bert-2.0
-"""
+"""Meta's w2vBERT based speaker embedding."""
 from typing import Optional
 
 import torch

test.py

@@ -33,6 +33,5 @@ def test():
     print(v.shape)
 
 
-
 if __name__ == '__main__':
     test()