tedlium-long-form / README.md
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---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: speaker_id
dtype: string
splits:
- name: validation
num_bytes: 180166870.0
num_examples: 8
- name: test
num_bytes: 285138900.0
num_examples: 12
download_size: 465034174
dataset_size: 465305770.0
---
# Dataset Card for "tedlium-long-form"
To create the dataset:
```python
import os
import numpy as np
from datasets import load_dataset, DatasetDict, Dataset, Audio
import soundfile as sf
from tqdm import tqdm
tedlium = load_dataset("LIUM/tedlium", "release3")
merged_dataset = DatasetDict()
validation_speaker_ids = [
"Al_Gore",
"Barry_Schwartz",
"Blaise_Agueray_Arcas",
"Brian_Cox",
"Craig_Venter",
"David_Merrill",
"Elizabeth_Gilbert",
"Wade_Davis",
]
validation_dataset_merged = {speaker_id: {"audio": [], "text": ""} for speaker_id in validation_speaker_ids}
test_speaker_ids = [
"AimeeMullins",
"BillGates",
"DanBarber",
"DanBarber_2010_S103",
"DanielKahneman",
"EricMead_2009P_EricMead",
"GaryFlake",
"JamesCameron",
"JaneMcGonigal",
"MichaelSpecter",
"RobertGupta",
]
test_dataset_merged = {speaker_id: {"audio": [], "text": ""} for speaker_id in test_speaker_ids}
for split, dataset in zip(["validation", "test"], [validation_dataset_merged, test_dataset_merged]):
sampling_rate = tedlium[split].features["audio"].sampling_rate
for sample in tqdm(tedlium[split]):
if sample["speaker_id"] in dataset:
dataset[sample["speaker_id"]]["audio"].extend(sample["audio"]["array"])
dataset[sample["speaker_id"]]["text"] += " " + sample["text"]
audio_paths = []
os.makedirs(split, exist_ok=True)
for speaker in dataset:
path = os.path.join(split, f"{speaker}-merged.wav")
audio_paths.append(path)
sf.write(path, np.asarray(dataset[speaker]["audio"]), samplerate=sampling_rate)
merged_dataset[split] = Dataset.from_dict({"audio": audio_paths}).cast_column("audio", Audio())
# remove spaced apostrophes (e.g. it 's -> it's)
merged_dataset[split] = merged_dataset[split].add_column("text", [dataset[speaker]["text"].replace(" '", "'") for speaker in dataset])
merged_dataset[split] = merged_dataset[split].add_column("speaker_id", dataset.keys())
```