--- language: [de, en, fr, ja, ko, zh] license: cc-by-nc-4.0 pretty_name: Emilia ERT size_categories: - 1M ## Files and audio addressing ```text . ├── audio/ │ ├── DE-B000000.tar │ ├── EN-B000000.tar │ └── ... ├── metrics.scp ├── SHA256SUMS ├── LICENSE └── README.md ``` `metrics.scp` is a UTF-8, TAB-separated table with a header, despite its extension. It is not a conventional two-column Kaldi SCP. Column order, values, precision, and source missing-value markers were preserved; only `path` was converted to a repository-relative locator: ```text audio/DE-B000000.tar:512:154989 ``` The components are **TAR path : byte offset : byte length**. The offset points to the encoded MP3 payload, not the TAR header. Archive members retain their local numeric names; `uid` supplies the original-style Emilia identifier. Archives were retained byte-for-byte without re-encoding during release preparation. Do not recompress or rebuild them while using these offsets. ## Metadata fields Types describe valid values; all cells are stored as text. Handle missing or nonnumeric markers explicitly rather than converting them to zero. Related outputs are grouped into a single metric entry below; column numbers refer to the unchanged 34-column SCP schema. | # | Field | Type / unit | Meaning | | ---: | --- | --- | --- | | 1 | `datasets` | string | Local source label; `Emilia_complete` throughout this release. | | 2 | `uid` | string | Segment identifier, e.g. `DE_B00008_S00023_W000000`; the prefix identifies the source language. | | 3 | `fs` | integer, Hz | Sample rate recorded in the source manifest. Scoring models may internally resample audio. | | 4 | `path` | string | Relative TAR path, payload offset, and payload length, separated by colons. | | 5 | `length(s)` | float, seconds | Segment duration from the source table. | | 6 | `silerovad` | float, fraction | Silero VAD detected-speech duration divided by total duration. | | 7 | `webrtcvad` | float, fraction | Speech fraction estimated by the WebRTC VAD workflow. | | 8 | `transcript` | string | Automatic transcript from the local WhisperX workflow; not a verified human transcription. | | 9 | `confidence` | float, score | Mean of available WhisperX aligned-word scores in the inspected implementation; not a calibrated probability of transcript correctness. | | 10 | `dnsmos` | float, predicted MOS | DNSMOS overall quality output (`DNSMOS_OVRL`). | | 11 | `scoreq` | float, model score | SCOREQ speech-quality estimate on the model's native scale. | | 12–14 | `squim_pesq`, `squim_sisdr`, `squim_stoi` | float; PESQ score, SI-SDR in dB, STOI score | Non-intrusive estimates of perceptual speech quality (PESQ), scale-invariant signal-to-distortion ratio (SI-SDR), and short-time objective intelligibility (STOI), respectively. These are model predictions without a clean reference. | | 15 | `srmr` | float, ratio | Speech-to-reverberation modulation energy ratio, a non-intrusive reverberation-related measure. | | 16 | `vqscore` | float, model score | VQScore non-intrusive speech-quality estimate. | | 17 | `wadasnr` | float, dB | Signal-to-noise ratio estimated using waveform amplitude distribution analysis (WADA-SNR). | | 18 | `distillmos` | float, predicted MOS | DistillMOS speech-quality estimate. | | 19 | `utmos` | float, predicted MOS | UTMOS speech-quality estimate. | | 20 | `dnsmos_pro` | float, model score | DNSMOS Pro quality output retained from the local scoring workflow. | | 21 | `nisqa` | float, predicted MOS | NISQA overall quality estimate (`NISQA_MOS`). | | 22–28 | `sigmos_ovrl`, `sigmos_col`, `sigmos_disc`, `sigmos_loud`, `sigmos_noise`, `sigmos_reverb`, `sigmos_sig` | float, predicted quality ratings | Ratings for overall quality, coloration, discontinuity, loudness, background noise, reverberation, and speech-signal quality, respectively. These are predicted quality dimensions, not physical impairment measurements. | | 29 | `ced` | float, probability score | Maximum CED probability over the workflow's selected noise/event classes. | | 30 | `flexsed` | float, probability score | Maximum FlexSED probability over selected noise/event prompts and time frames in the inspected workflow. | | 31 | `panns` | float, probability score | Maximum PANNs clip-level probability over selected classes at AudioSet. | | 32 | `beats` | string | BEATs highest-scoring selected non-speech event label followed by its score, e.g. `Inside, small room 0.0067`. Split from the right to extract the final numeric score. | | 33–34 | `speaker_count`, `overlap_ratio` | integer count; float fraction | Both are derived from Sortformer diarization outputs. `speaker_count` respents the number of speakers in the audio and `overlap_ratio` represents the degree of overlap between the speakers. | ## Usage Download `metrics.scp` and the required shards, then parse with an explicit TAB delimiter. Plain whitespace splitting would corrupt transcripts and event labels. ```python import csv from pathlib import Path root = Path("/path/to/Emilia_ERT") with (root / "metrics.scp").open(encoding="utf-8", newline="") as f: row = next(csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)) relative, offset, size = row["path"].rsplit(":", 2) with (root / relative).open("rb") as f: f.seek(int(offset)) audio_bytes = f.read(int(size)) assert len(audio_bytes) == int(size) print(row["uid"], row["transcript"]) # Optional MP3 decoding with a compatible libsndfile installation: # import io # import soundfile as sf # waveform, sample_rate = sf.read(io.BytesIO(audio_bytes)) ``` ## License and access review [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en) permits noncommercial sharing and adaptation within the licensor's rights, subject to attribution, a license reference, retention of supplied notices, and indication of changes. It does not independently clear third-party rights. See [LICENSE](LICENSE) for the attribution notice.