dev-ansh-r/supertonic2-qualcomm-quantized
By dev-ansh-r · ↓ 0 · ♥ 0 · Updated 2026-02-16
What's in this repo
This page lists the files in dev-ansh-r/supertonic2-qualcomm-quantized, including duration_predictor.onnx, text_encoder.onnx, vector_estimator.onnx and more.
- 4 ONNX models (.onnx files)
- 1876 files, including 929 .json, 911 .raw, 8 .txt, 4 .so, 4 .bin, 4 .cpp
- Last updated 2026-02-16
ONNX files
| File | Size | Download |
|---|---|---|
| model/onnx/duration_predictor.onnx | — | Download |
| model/onnx/text_encoder.onnx | — | Download |
| model/onnx/vector_estimator.onnx | — | Download |
| model/onnx/vocoder.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Note: This repository is a work in progress. The README will be updated with more details on the QCS6490 porting process, model architecture, and calibration data generation workflow in the coming weeks. Please check back for updates!
Supertonic-2 QNN Inference
High-quality Text-to-Speech synthesis using Supertonic-2 QNN models.
Quick Start
# Basic usage
python supertonic_inference.py --text "Hello world" --voice M1 -o output.wav
# With specific seed for reproducibility
python supertonic_inference.py \
--text "Your text here" \
--voice F1 \
--seed 42 \
--output output.wav
Features
- ✅ High Quality: Matches official Supertonic library behavior
- ✅ Reproducible: Use
--seedfor consistent outputs - ✅ Multilingual: Supports 5 languages (EN, KO, ES, PT, FR)
- ✅ Multiple Voices: 10 voice styles (5 female, 5 male)
- ✅ Customizable: Adjust quality, speed, and more
QCS6490 Deployment
This repository includes complete resources for porting to Qualcomm QCS6490 (Hexagon HTP V68):
- QCS6490 Porting Guide - Step-by-step deployment guide
- Architecture Deep Dive - Complete model architecture documentation
- Calibration Data Guide - Quantization and validation workflow
Generate Calibration Data
# Generate 10 calibration samples for quantization and accuracy validation
python generate_calibration_data.py
# Validate QNN model accuracy against ONNX reference
python validate_qnn_accuracy.py \
--calibration-dir calibration_data \
--qnn-dir qnn_outputs \
--report accuracy_report.json
Expected Performance on QCS6490:
- 100-150× real-time inference speed
- ~75ms latency for 2-second audio (5 diffusion steps)
- ~70-100 MB total model size (after INT8/FP16 quantization)
Model Files
Required directory structure:
model/
├── onnx/
│ ├── text_encoder.onnx
│ ├── duration_predictor.onnx
│ ├── vector_estimator.onnx
│ ├── vocoder.onnx
│ ├── tts.json
│ └── unicode_indexer.json
└── voice_styles/
├── F1.json ... F5.json (Female voices)
└── M1.json ... M5.json (Male voices)
Command Line Options
| Option | Description | Default |
|---|---|---|
--text, -t |
Text to synthesize | Required |
--voice, -v |
Voice style (F1-F5, M1-M5) | M1 |
--lang, -l |
Language (en, ko, es, pt, fr) | en |
--output, -o |
Output WAV file path | output/output.wav |
--steps |
Diffusion steps (more = better) | 10 |
--speed |
Speech speed multiplier | 1.0 |
--seed |
Random seed (for reproducibility) | None |
--quiet, -q |
Suppress progress messages | False |
Examples
Basic Synthesis
python supertonic_inference.py \
--text "The weather is nice today." \
--voice F1 \
--output weather.wav
High Quality with Reproducible Output
python supertonic_inference.py \
--text "Important announcement." \
--voice M1 \
--steps 20 \
--seed 42 \
--output announcement.wav
Faster Speech
python supertonic_inference.py \
--text "Quick update message." \
--voice F2 \
--speed 1.2 \
--output quick.wav
Spanish Language
python supertonic_inference.py \
--text "Hola mundo" \
--lang es \
--voice M3 \
--output spanish.wav
Voice Styles
| Code | Type | Description |
|---|---|---|
| F1-F5 | Female | 5 distinct female voices |
| M1-M5 | Male | 5 distinct male voices |
Supported Languages
en- Englishko- Koreanes- Spanishpt- Portuguesefr- French
Python API
from supertonic_inference import SupertonicTTS, save_wav
# Initialize
tts = SupertonicTTS(model_dir="model/onnx")
# Synthesize
waveform, duration = tts.synthesize(
text="Hello world",
voice_name="M1",
lang="en",
diffusion_steps=10,
speed=1.0,
seed=42
)
# Save
save_wav("output.wav", waveform, tts.sample_rate)
Performance
- Speed: ~25× faster than real-time on CPU
- Quality: Matches official Supertonic library
- Sample Rate: 44.1 kHz
- Variance: ~5% duration variance due to diffusion randomness
Parameters Guide
Diffusion Steps
- 5-10 steps: Fast, good quality (default: 10)
- 15-20 steps: Higher quality, slower
- Trade-off: Each step improves quality but increases compute time
Speed
- 0.8-1.0: Slower, more natural
- 1.0: Normal speed (default)
- 1.1-1.5: Faster, still intelligible
Seed
- None: Different output each run (random)
- Integer: Reproducible output with same seed
- Use case: Testing, demos, consistent results
Project Structure
supertonic2-qualcomm/
├── supertonic_inference.py # Main inference script
├── README.md # This file
├── model/
│ ├── onnx/ # ONNX models
│ └── voice_styles/ # Voice embeddings
├── inputs/ # Test inputs
└── output/ # Generated audio
Notes
- Text is automatically preprocessed (normalization, punctuation)
- Periods are added automatically if missing
- Unicode characters are handled transparently
- Emoji are automatically removed
License
This implementation uses models from Supertone/supertonic-2.
Reference
Official repository: https://github.com/supertone-inc/supertonic
Model info
onnx
text-to-speech
qualcomm
qnn
quantized
base_model:Supertone/supertonic-2
base_model:quantized:Supertone/supertonic-2
license:mit
region:us
↓ 0
♥ 0
Created: 2026-02-16
Updated: 2026-02-16
View on Hugging FaceFiles (1876)
.claude/settings.local.json
.gitattributes
.gitignore
HUGGINGFACE_UPLOAD.md
QNN_Model_lib/aarch64-oe-linux-gcc11.2/libduration_predictor_htp.so
QNN_Model_lib/aarch64-oe-linux-gcc11.2/libtext_encoder_htp.so
QNN_Model_lib/aarch64-oe-linux-gcc11.2/libvector_estimator_htp.so
QNN_Model_lib/aarch64-oe-linux-gcc11.2/libvocoder_htp.so
QNN_Models/duration_predictor_htp.bin
QNN_Models/duration_predictor_htp.cpp
QNN_Models/duration_predictor_htp_net.json
QNN_Models/text_encoder_htp.bin
QNN_Models/text_encoder_htp.cpp
QNN_Models/text_encoder_htp_net.json
QNN_Models/vector_estimator_htp.bin
QNN_Models/vector_estimator_htp.cpp
QNN_Models/vector_estimator_htp_net.json
QNN_Models/vocoder_htp.bin
QNN_Models/vocoder_htp.cpp
QNN_Models/vocoder_htp_net.json
README.md
Step1_Supertonic2_QNN_Porting.ipynb
board_outputs/samples/final_reference_output.wav
calibration_data/calibration_summary.json
calibration_data/duration_predictor_input_list.txt
calibration_data/sample_001/duration_predictor/input_style_dp.raw
calibration_data/sample_001/duration_predictor/input_style_dp.shape.json
calibration_data/sample_001/duration_predictor/input_text_ids.raw
calibration_data/sample_001/duration_predictor/input_text_ids.shape.json
calibration_data/sample_001/duration_predictor/input_text_mask.raw
calibration_data/sample_001/duration_predictor/input_text_mask.shape.json
calibration_data/sample_001/duration_predictor/output_duration.raw
calibration_data/sample_001/duration_predictor/output_duration.shape.json
calibration_data/sample_001/metadata.json
calibration_data/sample_001/text_encoder/input_style_ttl.raw
calibration_data/sample_001/text_encoder/input_style_ttl.shape.json
calibration_data/sample_001/text_encoder/input_text_ids.raw
calibration_data/sample_001/text_encoder/input_text_ids.shape.json
calibration_data/sample_001/text_encoder/input_text_mask.raw
calibration_data/sample_001/text_encoder/input_text_mask.shape.json
calibration_data/sample_001/text_encoder/output_text_emb.raw
calibration_data/sample_001/text_encoder/output_text_emb.shape.json
calibration_data/sample_001/vector_estimator/step_000/input_current_step.raw
calibration_data/sample_001/vector_estimator/step_000/input_current_step.shape.json
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calibration_data/sample_001/vector_estimator/step_000/input_style_ttl.raw
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calibration_data/sample_001/vector_estimator/step_001/input_style_ttl.raw
calibration_data/sample_001/vector_estimator/step_001/input_style_ttl.shape.json
calibration_data/sample_001/vector_estimator/step_001/input_text_emb.raw
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calibration_data/sample_001/vocoder/output_waveform.raw
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calibration_data/sample_002/duration_predictor/input_text_ids.raw
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calibration_data/sample_002/text_encoder/input_text_ids.raw
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calibration_data/sample_009/vector_estimator/step_009/input_text_emb.shape.json
calibration_data/sample_009/vector_estimator/step_009/input_text_mask.raw
calibration_data/sample_009/vector_estimator/step_009/input_text_mask.shape.json
calibration_data/sample_009/vector_estimator/step_009/input_total_step.raw
calibration_data/sample_009/vector_estimator/step_009/input_total_step.shape.json
calibration_data/sample_009/vector_estimator/step_009/output_latent.raw
calibration_data/sample_009/vector_estimator/step_009/output_latent.shape.json
calibration_data/sample_009/vocoder/input_latent.raw
calibration_data/sample_009/vocoder/input_latent.shape.json
calibration_data/sample_009/vocoder/output_waveform.raw
calibration_data/sample_009/vocoder/output_waveform.shape.json
calibration_data/sample_010/duration_predictor/input_style_dp.raw
calibration_data/sample_010/duration_predictor/input_style_dp.shape.json
calibration_data/sample_010/duration_predictor/input_text_ids.raw
calibration_data/sample_010/duration_predictor/input_text_ids.shape.json
calibration_data/sample_010/duration_predictor/input_text_mask.raw
calibration_data/sample_010/duration_predictor/input_text_mask.shape.json
calibration_data/sample_010/duration_predictor/output_duration.raw
calibration_data/sample_010/duration_predictor/output_duration.shape.json
calibration_data/sample_010/metadata.json
calibration_data/sample_010/text_encoder/input_style_ttl.raw
calibration_data/sample_010/text_encoder/input_style_ttl.shape.json
calibration_data/sample_010/text_encoder/input_text_ids.raw
calibration_data/sample_010/text_encoder/input_text_ids.shape.json
calibration_data/sample_010/text_encoder/input_text_mask.raw
calibration_data/sample_010/text_encoder/input_text_mask.shape.json
calibration_data/sample_010/text_encoder/output_text_emb.raw
calibration_data/sample_010/text_encoder/output_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_000/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_000/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_000/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_000/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_000/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_000/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_000/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_000/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_000/output_latent.raw
calibration_data/sample_010/vector_estimator/step_000/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_001/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_001/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_001/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_001/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_001/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_001/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_001/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_001/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_001/output_latent.raw
calibration_data/sample_010/vector_estimator/step_001/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_002/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_002/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_002/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_002/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_002/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_002/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_002/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_002/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_002/output_latent.raw
calibration_data/sample_010/vector_estimator/step_002/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_003/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_003/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_003/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_003/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_003/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_003/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_003/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_003/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_003/output_latent.raw
calibration_data/sample_010/vector_estimator/step_003/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_004/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_004/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_004/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_004/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_004/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_004/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_004/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_004/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_004/output_latent.raw
calibration_data/sample_010/vector_estimator/step_004/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_005/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_005/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_005/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_005/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_005/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_005/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_005/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_005/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_005/output_latent.raw
calibration_data/sample_010/vector_estimator/step_005/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_006/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_006/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_006/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_006/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_006/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_006/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_006/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_006/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_006/output_latent.raw
calibration_data/sample_010/vector_estimator/step_006/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_007/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_007/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_007/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_007/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_007/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_007/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_007/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_007/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_007/output_latent.raw
calibration_data/sample_010/vector_estimator/step_007/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_008/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_008/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_008/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_008/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_008/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_008/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_008/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_008/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_008/output_latent.raw
calibration_data/sample_010/vector_estimator/step_008/output_latent.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_current_step.raw
calibration_data/sample_010/vector_estimator/step_009/input_current_step.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_latent_mask.raw
calibration_data/sample_010/vector_estimator/step_009/input_latent_mask.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_noisy_latent.raw
calibration_data/sample_010/vector_estimator/step_009/input_noisy_latent.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_style_ttl.raw
calibration_data/sample_010/vector_estimator/step_009/input_style_ttl.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_text_emb.raw
calibration_data/sample_010/vector_estimator/step_009/input_text_emb.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_text_mask.raw
calibration_data/sample_010/vector_estimator/step_009/input_text_mask.shape.json
calibration_data/sample_010/vector_estimator/step_009/input_total_step.raw
calibration_data/sample_010/vector_estimator/step_009/input_total_step.shape.json
calibration_data/sample_010/vector_estimator/step_009/output_latent.raw
calibration_data/sample_010/vector_estimator/step_009/output_latent.shape.json
calibration_data/sample_010/vocoder/input_latent.raw
calibration_data/sample_010/vocoder/input_latent.shape.json
calibration_data/sample_010/vocoder/output_waveform.raw
calibration_data/sample_010/vocoder/output_waveform.shape.json
calibration_data/text_encoder_input_list.txt
calibration_data/vector_estimator_input_list.txt
calibration_data/vocoder_input_list.txt
generate_calibration_data.py
inputs/current_step.raw
inputs/dur_pred_input.txt
inputs/latent.raw
inputs/latent_mask.raw
inputs/noisy_latent.raw
inputs/reference_output.wav
inputs/style_dp.raw
inputs/style_ttl.raw
inputs/text_emb.raw
inputs/text_enc_input.txt
inputs/text_ids.raw
inputs/text_mask.raw
inputs/total_step.raw
inputs/vec_est_input.txt
inputs/vocoder_input.txt
inputs/wav_reference.raw
model/config.json
model/onnx/duration_predictor.onnx
ONNX
model/onnx/text_encoder.onnx
ONNX
model/onnx/tts.json
model/onnx/unicode_indexer.json
model/onnx/vector_estimator.onnx
ONNX
model/onnx/vocoder.onnx
ONNX
model/voice_styles/F1.json
model/voice_styles/F2.json
model/voice_styles/F3.json
model/voice_styles/F4.json
model/voice_styles/F5.json
model/voice_styles/M1.json
model/voice_styles/M2.json
model/voice_styles/M3.json
model/voice_styles/M4.json
model/voice_styles/M5.json
output/custom.wav
run_qnn_tts_pipeline.py
supertonic_architecture.md
supertonic_inference.py
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