release

SpeechTaxi.py

@@ -15,9 +15,7 @@ NAMES = [
     "bgc",
     "bht",
     "ckb",
-    "eng",
     "ewe",
-    "fra",
     "guj",
     "ibo",
     "kan",
@@ -30,7 +28,6 @@ NAMES = [
     "nlx",
     "pan",
     "peg",
-    "rus",
     "tam",
     "tel",
     "tw-akuapem",
@@ -42,9 +39,17 @@ NAMES = [
     
 ]
 
-DESCRIPTION = ""
-CITATION = "TODO"
-HOMPAGE = "github.com/LennartKeller"
+DESCRIPTION = """"""
+CITATION = """@misc{keller2024speechtaximultilingualsemanticspeech,
+      title={SpeechTaxi: On Multilingual Semantic Speech Classification}, 
+      author={Lennart Keller and Goran Glavaš},
+      year={2024},
+      eprint={2409.06372},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2409.06372}, 
+}"""
+HOMPAGE = "https://huggingface.co/datasets/LennartKeller/SpeechTaxi"
 
 class SpeechTaxiConfig(datasets.BuilderConfig):
     def __init__(
@@ -88,9 +93,8 @@ class SpeechTaxi(datasets.GeneratorBasedBuilder):
                         ]
                     ),
                     "audio": datasets.features.Audio(sampling_rate=16_000),
-                    "transription_mms-zeroshot-300m": datasets.features.Value("string"),
-                    "transription_mms": datasets.features.Value("string"),
-                    "transription_whisper-large-v3": datasets.features.Value("string"),
+                    "transcription_mms-zeroshot-300m": datasets.features.Value("string"),
+                    "transcription_whisper-large-v3": datasets.features.Value("string"),
                 }
             ),
             supervised_keys=None,

create_release.py

@@ -16,8 +16,18 @@ from tqdm.auto import tqdm
 NAME = "SpeechTaxi"
 VERSION = "0.0.1"
 HOMEPAGE = "github.com/LennartKeller"
-CITATION = "TODO"
-DESCRIPTION = "TODO"
+CITATION = """
+@misc{keller2024speechtaximultilingualsemanticspeech,
+      title={SpeechTaxi: On Multilingual Semantic Speech Classification}, 
+      author={Lennart Keller and Goran Glavaš},
+      year={2024},
+      eprint={2409.06372},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2409.06372}, 
+}
+""".strip()
+DESCRIPTION = "Multlingual Semantic Speech Classification"
 SAVE_DIR = Path("/hdd/lennart/datasets")
 
 # Define some arguments and 'constants'
@@ -28,11 +38,13 @@ REWRITE_PATHS = (
 )
 REWRITE_MASS_PATHS = ("/Volumes/SanDiskData/", "/hdd/lennart/")
 ALIGNED_TABLES_DIR = Path("aligned_tables")
-INCLUDE_MASS_LANGUAGES = True
+INCLUDE_MASS_LANGUAGES = False
 MASS_LANGUAGES = ("eng", "rus", "spa", "ron", "eus", "fra")
 SKIP_LANGUAGES = ("ron", "eus", "spa", "hau", "bdv", "nep", "ben")
 SCRIPT_TEMPLATE = Path("SpeechTaxi.py.jinja")
 
+if not INCLUDE_MASS_LANGUAGES:
+    SKIP_LANGUAGES += MASS_LANGUAGES
 
 def rewrite_path(p: str | Path) -> str | Path:
     if REWRITE_PATHS:
@@ -213,7 +225,7 @@ def read_mass_instance(audio_file: str | Path) -> dict:
         key = machine_generated_transcription_file.stem.split("_one_channel-")[-1]
         key = key.removesuffix("-transcript")
         # print(audio_file, "|", machine_generated_transcription_file, "|", key)
-        machine_generated_transcriptions[f"transription_{key}"] = (
+        machine_generated_transcriptions[f"transcription_{key}"] = (
             machine_generated_transcription_file.read_text()
         )
     data = {
@@ -266,8 +278,10 @@ def read_bible_scrape_instance(audio_file: str | Path) -> dict:
             .removesuffix("-transcript")
             .strip("-")
         )
+        # if key.endswith("mms"):
+        #     continue
         # print(audio_file, "|", machine_generated_transcription_file, "|", key)
-        machine_generated_transcriptions[f"transription_{key}"] = (
+        machine_generated_transcriptions[f"transcription_{key}"] = (
             machine_generated_transcription_file.read_text()
         )
 
@@ -344,7 +358,7 @@ if __name__ == "__main__":
                 except Exception as e:
                     print("Error reading file", audio_file)
                     print(e)
-                    print("_"*30)
+                    print("_" * 30)
                     continue
                 # Files that can't be read have zero alignment scores anyways so in most cases this isn't an issue
                 data = (
@@ -366,7 +380,7 @@ if __name__ == "__main__":
                 except Exception as e:
                     print("Error reading file", audio_file)
                     print(e)
-                    print("_"*30)
+                    print("_" * 30)
                     continue
                 # Files that can't be read have zero alignment scores anyways so in most cases this isn't an issue
                 data = data | {
@@ -376,8 +390,10 @@ if __name__ == "__main__":
                     "audio": copied_audio_file.relative_to(data_dir).as_posix(),
                 }
                 final_table_data.append(data)
-            pbar.set_description(f"{str(alignment_table)} | Total invalid: {invalid_counter}")
-        
+            pbar.set_description(
+                f"{str(alignment_table)} | Total invalid: {invalid_counter}"
+            )
+
         final_table = pd.DataFrame.from_records(final_table_data)
         final_table.to_csv(table_dir / alignment_table.name, index=False, sep="\t")
 

data.zip

@@ -1,3 +1,3 @@
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-size 2905453052
+oid sha256:e14e207cb519590033888b4b2f4c26c5f7f631c288f5e84ea2e5b3d4ed648592
+size 1781086177

tables.zip

@@ -1,3 +1,3 @@
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-oid sha256:6b4ac7fc8d111d463295402b1469117ef74ba5bdfa7ddc5b9a2fae3fef2f4306
-size 7586373
+oid sha256:5d31472713cba7263aefd92133953bc0096a8c7175e27bcae669264297080e2b
+size 6999392