README.md

---
dataset_info:
  features:
  - name: sequence
    dtype: string
  - name: transcription_full
    dtype: string
  - name: transcription_original
    dtype: string
  - name: removed_words
    dtype: string
  - name: phonemes_annotated
    dtype: string
  - name: to_convert
    dtype: string
  - name: edit_type
    dtype: string
  - name: phoneme_probability
    dtype: float64
  - name: xcodec2_tokens
    dtype: string
  splits:
  - name: train
    num_bytes: unknown
    num_examples: 301979
  download_size: unknown
  dataset_size: unknown
---

# Multilingual Audio Alignments - Processed (Mixed Text/Phonemes)

This dataset contains processed audio alignments from AAdonis/multilingual_audio_alignments (french).

## Curriculum Learning

This dataset uses **mixed text/phoneme conditioning** with a curriculum learning schedule:
- **p_start**: 0.0 (starting probability of using phonemes)
- **p_end**: 0.0 (ending probability of using phonemes)
- **curriculum_rows**: 400000 (rows over which probability increases)

Early in the dataset, more words are kept as text. Later, almost all words are converted to phonemes.

## Deletion Training

**Deletion ratio**: 20.0% of samples are deletion samples
**Deletion margin**: 0.1s on each side (=0.2s total transition)

How deletion training works:
1. Pick a random gap between two adjacent words
2. Find the midpoint of that gap
3. Cut 0.1s on each side of the midpoint
4. The target audio is that 0.2s transition
5. The phoneme content is `<|ph_space|>`
6. The transcript remains unchanged (no words removed)

This teaches the model to generate natural inter-word transitions.

## Features:
- `sequence`: Full LLASA training sequence with mixed text/phonemes and XCodec2 tokens
- `transcription_full`: Transcript matching the actual audio (left + right portions)
- `transcription_original`: Original full transcript
- `removed_words`: Words that were removed for infilling training (empty for deletion)
- `phonemes_annotated`: Mixed text/phoneme tokens with markers
- `to_convert`: Type of conditioning: "text", "phonemes", or "text and phonemes"
- `edit_type`: Type of edit: "substitution" or "deletion"
- `phoneme_probability`: The probability used for this sample (for debugging)
- `xcodec2_tokens`: XCodec2 audio token representations

## Sequence Format:
```
{mixed_left}<|start_phon_gen|>{mixed_removed}<|end_phon_gen|>{mixed_right}<|start_audio|>{right_audio}<|start_of_speech|>{left_audio}<|SPEECH_GENERATION_START|>{removed_audio}<|SPEECH_GENERATION_END|>
```

Note: The training script adds the instruction prefix ("Generate the missing speech from..."), so it's not included in the data.
The XCodec2 audio tokens are UNCHANGED - only the text/phoneme conditioning is mixed.
**ALL segments (left, removed, right) use the same curriculum probability** - so with p=0 you get pure text, with p=1 pure phonemes.

## Processing:
- Language: french
- Index range: 0 to 99999
- Final row counter: 301979
- Total samples: 301979