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README.md

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+---
+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: 522013
+  download_size: unknown
+  dataset_size: unknown
+---
+
+# Multilingual Audio Alignments - Processed (Mixed Text/Phonemes)
+
+This dataset contains processed audio alignments from AAdonis/multilingual_audio_alignments (mandarin).
+
+## 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: mandarin
+- Index range: 540000 to 714787
+- Final row counter: 522013
+- Total samples: 522013