| import os |
| from collections import Counter |
|
|
| import numpy as np |
| import soundfile as sf |
| from datasets import load_dataset |
|
|
| dataset = load_dataset( |
| "parquet", |
| data_files={ |
| "train": [ |
| "data/test-00000-of-00017.parquet", |
| "data/test-00001-of-00017.parquet", |
| "data/test-00002-of-00017.parquet", |
| "data/test-00003-of-00017.parquet", |
| "data/test-00004-of-00017.parquet", |
| "data/test-00005-of-00017.parquet", |
| "data/test-00006-of-00017.parquet", |
| "data/test-00007-of-00017.parquet", |
| "data/test-00008-of-00017.parquet", |
| "data/test-00009-of-00017.parquet", |
| "data/test-00010-of-00017.parquet", |
| "data/test-00011-of-00017.parquet", |
| "data/test-00012-of-00017.parquet", |
| "data/test-00013-of-00017.parquet", |
| "data/test-00014-of-00017.parquet", |
| "data/test-00015-of-00017.parquet", |
| "data/test-00016-of-00017.parquet", |
| ] |
| } |
| ) |
|
|
| MAX_DURATION = 60.0 |
| MAX_SPEAKERS = 4 |
|
|
|
|
| def crop_longest_60s(example): |
| starts = example["timestamps_start"] |
| ends = example["timestamps_end"] |
| speakers = example["speakers"] |
| n = len(starts) |
|
|
| best_left, best_right, best_dur = 0, 0, 0 |
| left = 0 |
| spk_count = Counter() |
| for right in range(n): |
| spk_count[speakers[right]] += 1 |
| while left <= right and (ends[right] - starts[left] > MAX_DURATION or len(spk_count) > MAX_SPEAKERS): |
| spk_count[speakers[left]] -= 1 |
| if spk_count[speakers[left]] == 0: |
| del spk_count[speakers[left]] |
| left += 1 |
| if left > right: |
| continue |
| dur = ends[right] - starts[left] |
| if dur > best_dur: |
| best_dur = dur |
| best_left, best_right = left, right |
|
|
| sr = example["audio"]["sampling_rate"] |
| start_sample = int(starts[best_left] * sr) |
| end_sample = int(ends[best_right] * sr) |
| offset = starts[best_left] |
|
|
| example["audio"]["array"] = example["audio"]["array"][start_sample:end_sample] |
| example["timestamps_start"] = [t - offset for t in starts[best_left:best_right + 1]] |
| example["timestamps_end"] = [t - offset for t in ends[best_left:best_right + 1]] |
| example["speakers"] = example["speakers"][best_left:best_right + 1] |
| return example |
|
|
|
|
| filenames = [os.path.basename(example["audio"]["path"]) for example in dataset["train"]] |
|
|
| dataset["train"] = dataset["train"].map(crop_longest_60s) |
|
|
| os.makedirs("wavs", exist_ok=True) |
| for i, example in enumerate(dataset["train"]): |
| audio = example["audio"] |
| filename = filenames[i] |
| duration = len(audio["array"]) / audio["sampling_rate"] |
| sf.write(f"wavs/{filename}", np.array(audio["array"]), audio["sampling_rate"]) |
| num_speakers = len(set(example["speakers"])) |
| print(f"[{i + 1}/16] Saved wavs/{filename}, duration: {duration:.2f}s, segments: {len(example['timestamps_start'])}, speakers: {num_speakers}") |
