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[The moon] I gazed with a kind of wonder.
[The moon] I gazed with a kind of wonder.
730
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"I gradually saw plainly the clear stream that supplied me with drink and the trees that shaded me w(...TRUNCATED)
"I gradually saw plainly the clear stream that supplied me with drink and the trees that shaded me w(...TRUNCATED)
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I examined the materials of the fire, and to my joy found it to be composed of wood.
I examined the materials of the fire, and to my joy found it to be composed of wood.
730
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float16
I quickly collected some branches, but they were wet and would not burn.
I quickly collected some branches, but they were wet and would not burn.
730
"/root/.cache/huggingface/datasets/downloads/extracted/38ec98f3d30a82fb2d9844979481e0c2be8bf568f3496(...TRUNCATED)
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"The vegetables in the gardens, the milk and cheese that I saw placed at the windows of some of the (...TRUNCATED)
"The vegetables in the gardens, the milk and cheese that I saw placed at the windows of some of the (...TRUNCATED)
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"I ate my breakfast with pleasure and was about to remove a plank to procure myself a little water w(...TRUNCATED)
"I ate my breakfast with pleasure and was about to remove a plank to procure myself a little water w(...TRUNCATED)
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"One was old, with silver hairs and a countenance beaming with benevolence and love; the younger was(...TRUNCATED)
"One was old, with silver hairs and a countenance beaming with benevolence and love; the younger was(...TRUNCATED)
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"The old man returned to the cottage, and the youth, with tools different from those he had used in (...TRUNCATED)
"The old man returned to the cottage, and the youth, with tools different from those he had used in (...TRUNCATED)
730
"/root/.cache/huggingface/datasets/downloads/extracted/38ec98f3d30a82fb2d9844979481e0c2be8bf568f3496(...TRUNCATED)
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"Before I had quitted your apartment, on a sensation of cold, I had covered myself with some clothes(...TRUNCATED)
"Before I had quitted your apartment, on a sensation of cold, I had covered myself with some clothes(...TRUNCATED)
730
"/root/.cache/huggingface/datasets/downloads/extracted/38ec98f3d30a82fb2d9844979481e0c2be8bf568f3496(...TRUNCATED)
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730_358_000002_000001
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float16
"\"It was dark when I awoke; I felt cold also, and half frightened, as it were, instinctively, findi(...TRUNCATED)
"\"It was dark when I awoke; I felt cold also, and half frightened, as it were, instinctively, findi(...TRUNCATED)
730
"/root/.cache/huggingface/datasets/downloads/extracted/38ec98f3d30a82fb2d9844979481e0c2be8bf568f3496(...TRUNCATED)
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730_358_000002_000000
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float16
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Processed and packed librittsr spectrograms

Simple packed librittsr dataset for quick tests. Contains text and spectrograms for all audio

Parquet shards summary

statistic text_normalized text_original speaker_id path chapter_id id mel mel_shape mel_dtype
str str str str str str str str f64 str
count 374999 374999 374999 374999 374999 374999 374999 374999.0 374999
null_count 0 0 0 0 0 0 0 0.0 0
mean null null null null null null null null null
std null null null null null null null null null
min "" 'Are you the cashier?' "" "" 'Are you the cashier?' "" 100 /root/.cache/huggingface/datas… 1 1001_134708_000013_... b'\x00\x17$?\x01?\xe4;... null float16
25% null null null null null null null null null
50% null null null null null null null null null
75% null null null null null null null null null
max {sixteen twenty five.} No soon… “’Tis young Mister Ladbruk,” s… 986 /root/.cache/huggingface/datas… 99912 98_199_000030_000000 b'\xff\xc7\xc7\xbf\x0f... null float16

Mel parameters

sample_rate=24_000
n_fft=1024
hop_length=256
win_length=1024
n_mels=100
center=True
power=1

To pack and unpack spectrograms

def to_mel_bytes(mel_db_t: "torch.Tensor") -> tuple[bytes, list[int], str]:
    if hasattr(mel_db_t, "detach"):
        mel_db_t = mel_db_t.detach()
    if mel_db_t.ndim == 3:
        mel_db_t = mel_db_t.squeeze(0)

    mel_np = (
        mel_db_t
        .to("cpu")
        .contiguous()
        .numpy()
        .astype(np.float16)
    )
    shape = list(mel_np.shape)
    return mel_np.tobytes(), shape, "float16"

def from_mel_bytes(mel_bytes: bytes, mel_shape: list[int], mel_dtype: str = "float16") -> np.ndarray:
    arr = np.frombuffer(mel_bytes, dtype=np.dtype(mel_dtype))
    return arr.reshape(mel_shape)
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