init

attach_speaker_embedding_s2s.py

@@ -59,6 +59,7 @@ print(f"Num examples (after filtering): {len(dataset)}")
 
 def speaker_embedding(example):
     for side in sides:
+        print(example[f"{side}.audio"]["array"].shape)
         embedding = speaker_embedder.get_speaker_embedding(
             example[f"{side}.audio"]["array"], example[f"{side}.audio"]["sampling_rate"]
         )

download_s2t_metadata.py

@@ -1,13 +1,5 @@
-import json
 import os
-import tarfile
-import zipfile
-import gzip
 import subprocess
-from os.path import join as p_join
-from tqdm import tqdm
-from multiprocessing import Pool
-from typing import Optional
 
 import pandas as pd
 

fetch_dataset_s2s.py

@@ -10,7 +10,6 @@ from tqdm import tqdm
 from multiprocessing import Pool
 from typing import Optional, Dict
 from glob import glob
-# import librosa
 
 import pandas as pd
 import soundfile as sf

main_s2s.sh

@@ -404,24 +404,15 @@ do
   python attach_speaker_embedding_s2s.py
 done
 
-
 export SE_MODEL="hubert-xl"  # running
-for i in 165 167;
-do
-  export DATASET_ID=${i}
-  export DIRECTION="enA-zhA"
-  python attach_speaker_embedding_s2s.py
-done
-
+export DATASET_ID=167
+export DIRECTION="enA-zhA"
+python attach_speaker_embedding_s2s.py
 
 export SE_MODEL="w2vbert-600m"  # running
-for i in 142 165 167 207 253;
-do
-  export DATASET_ID=${i}
-  export DIRECTION="enA-zhA"
-  python attach_speaker_embedding_s2s.py
-done
-
+export DATASET_ID=165
+export DIRECTION="enA-zhA"
+python attach_speaker_embedding_s2s.py