Update README from current release directory

README.md

@@ -11,9 +11,9 @@ tags: [audio, speech, speech-quality, speech-metrics, emilia]
 
 ## Dataset summary
 
-Emilia ERT contains **9,310,186 speech segments totaling 26,133.85 hours** in six languages, distributed as **666 audio TAR shards** and a single **34-column metadata table**, `metrics.scp`. The data originate from `emilia_complete` and were selected using the **SQA+SED filtering strategy described in the accompanying paper**, combining speech quality assessment (SQA) and sound event detection (SED). Existing transcripts and automatic audio metrics are included.
+Emilia ERT contains **9,310,186 speech segments totaling 26,133.85 hours** in six languages, distributed as **666 audio TAR shards** and a single **34-column metadata table**, `metrics.scp`. The data originate from [Emilia dataset](https://huggingface.co/datasets/amphion/Emilia-Dataset) and were selected using the **SQA+SED filtering strategy described in the accompanying paper**, combining speech quality assessment (SQA) and sound event detection (SED). Existing transcripts and automatic audio metrics are included.
+
 
-`Emilia_complete` identifies the local source collection; it does **not** mean this repository contains the complete upstream release. No additional English/Chinese-only selection was applied during release preparation. This is an independently prepared collection in the AudioCC-Lab namespace, not an official Amphion release.
 
 | Language | Code | Segments | Duration (hours) | TAR shards |
 | --- | --- | ---: | ---: | ---: |
@@ -27,13 +27,15 @@ Emilia ERT contains **9,310,186 speech segments totaling 26,133.85 hours** in si
 
 Durations are sums of the `length(s)` values in the released `metrics.scp`, converted to hours and rounded to two decimal places. All 9,310,186 records have numeric duration values.
 
-## Data source and filtering
+Audio archives occupy 665,879,367,680 bytes; `metrics.scp` occupies 6,134,693,898 bytes. No held-out evaluation split is provided. Define appropriate speaker/source-disjoint splits for experiments.
+
+<!-- ## Data source and filtering
 
 The source collection is `emilia_complete`, derived from the original [Emilia dataset](https://huggingface.co/datasets/amphion/Emilia-Dataset). This release contains the data retained after applying the paper's **SQA+SED** filtering strategy: SQA provides speech-quality measurements, while SED provides sound-event information used in the selection. The source is recorded as `Emilia_complete` in the `datasets` column. Emilia-YODAS is not included.
 
-Release preparation preserved the already selected audio and its metadata; it did not rerun the filtering strategy. The duration statistics above describe this filtered release.
+Release preparation preserved the already selected audio and its metadata; it did not rerun the filtering strategy. The duration statistics above describe this filtered release. -->
+
 
-Audio archives occupy 665,879,367,680 bytes; `metrics.scp` occupies 6,134,693,898 bytes. No held-out evaluation split is provided. Define appropriate speaker/source-disjoint splits for experiments.
 
 ## Files and audio addressing
 
@@ -74,7 +76,7 @@ Types describe valid values; all cells are stored as text. Handle missing or non
 | 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:** `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. |
+| 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). |
@@ -82,12 +84,12 @@ Types describe valid values; all cells are stored as text. Handle missing or non
 | 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:** `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 (AudioSet indices 72 onward). |
+| 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 indices 72 onward. |
+| 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 | **Sortformer:** `speaker_count`, `overlap_ratio` | integer count; float fraction | Both are derived from Sortformer diarization outputs. `speaker_count` counts speaker streams meeting minimum active-duration criteria. `overlap_ratio` is the fraction of all analyzed frames with at least two active streams after thresholding and short-run removal; its denominator is not restricted to speech frames. These are automatic estimates. |
+| 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. |