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microsoftspeecht5_tts

SpeechT5

Passes a reviewed speaker-embedding file through SpeechT5's safe public loader.

Text to speechVoiceHub-nativespeecht5Parameters: Not reportedLanguage: enTraining: nativeLicense: Checkpoint-specific

Parameter metadata: Not reported: the audited metadata available for the registered default does not provide an exact parameter total.

Use this model Checkpoint
Resources
Paper Upstream GitHub VoiceHub source Open in Colab

Usage

Complete the VoiceHub installation once, then run this repository-authored example. Model pages intentionally contain no package-install command.

This example is maintained against VoiceHub's public API; it is not copied from an upstream demo or package README.

Model-specific path: Passes a reviewed speaker-embedding file through SpeechT5's safe public loader.

Inputs and controls: Use Safetensors or NPY for embeddings; omit the field to use the wrapper's neutral zero embedding.

from pathlib import Path

from voicehub import AutoModelForTextToSpeech, TTSGenerationConfig

SPEAKER_EMBEDDING = Path("speaker_embedding.npy")
if not SPEAKER_EMBEDDING.is_file():
    raise FileNotFoundError(SPEAKER_EMBEDDING)

model = AutoModelForTextToSpeech.from_pretrained(
    'microsoft/speecht5_tts',
    model_type='speecht5',
    device="cuda",
    lazy_load=True,
)
output = model.generate(
    'VoiceHub keeps model integrations explicit and reproducible.',
    generation_config=TTSGenerationConfig(
        seed=42,
        output_file=Path("output.wav"),
    ),
    speaker_embedding_path=SPEAKER_EMBEDDING,
    threshold=0.5,
)
print(output.file_path, output.sample_rate, output.metadata)

Use authorized recordings. Verify hardware needs and pin a revision in production.

Overview

speecht5 is a VoiceHub text to speech integration. This page is generated from its registry contract. Open the speecht5 Colab notebook.

Property Value
Task Text to speech
Architecture speecht5
Runtime VoiceHub-native
Languages en
Capabilities text-to-speech, speaker-embedding, safetensors, fine-tuning, voicehub-native, native-runtime, raw-audio-fine-tuning, inference-reloadable-training-export
Reusable components —
Normalized output TTSOutput

Language support

Supported language abbreviations

en

Paper and GitHub

Configuration

Load configuration without constructing the model:

from voicehub import AutoConfig

config = AutoConfig.for_model('speecht5')
print(config.model_type)
Property Value
Canonical model type speecht5
Configuration class SpeechT5Config
Architecture class SpeechT5ForTextToSpeech

Processing

Create the registered processor without allocating model weights:

from voicehub import AutoProcessor

processor = AutoProcessor.from_pretrained(
    'microsoft/speecht5_tts',
    model_type='speecht5',
)
print(type(processor).__name__)

Inference

The Usage example returns TTSOutput through AutoModelForTextToSpeech.

Input and output contract

Property Value
Readiness integrated-raw
Data architecture sequence-to-sequence
Sample rate 16,000 Hz
Contract getter get_tts_dataset_spec('speecht5')
Variant Required fields One of Boundary Other rules
raw-audio text, audio — Source —
processor-ready input_ids, labels — Prepared —

Encoder text plus teacher-forced acoustic or codec targets. See the data workflow.

Training and optimization

Use available_optimization_passes() to discover reversible public passes. Unsupported runtime or hardware fails closed before mutation.

Training contract

Property Value
Support native
Family sequence-to-sequence
Recipe single-phase
Default phase spectrogram
Training checkpoint microsoft/speecht5_tts
Native training graph yes
Phase Kind Components Required inputs Loss keys
spectrogram objective model input_ids, attention_mask, labels loss

The integration accepts its declared source or prepared contract directly. Call model.validate_training_support() first, then follow the training workflow.

Checkpoints, provenance, license, and limitations

Property Value
Default checkpoint microsoft/speecht5_tts
Hugging Face ID microsoft/speecht5_tts
Repository availability verified through the Hugging Face model API on 2026-08-11; pin a revision before production use.
Checkpoint status Registry default; pin an immutable revision for production and reproducible evidence
Optional dependency extra Core package
Hardware and runtime Usage selects cuda; verify checkpoint-specific requirements
Real-checkpoint evidence Release evidence; a registry default alone is not execution evidence
Implementation voicehub.models.speecht5.modeling_speecht5.SpeechT5ForTextToSpeech
Configuration voicehub.models.speecht5.configuration_speecht5.SpeechT5Config
Source provenance voicehub/models/speecht5/SOURCE.json
License Checkpoint-specific

No VoiceHub-specific license override is registered. Verify the checkpoint and upstream source terms before use.

Confirm the checkpoint revision, access terms, provenance, and license.

Limitations

  • No integration-specific checkpoint limitation is registered. Verify the selected checkpoint revision and its documented runtime requirements.
  • Validate memory, precision, and optional dependencies on the target system.
  • Public optimizations fail closed when the runtime or hardware cannot satisfy their validation contract; an unavailable pass is not reported as applied.
  • Contract tests do not replace the linked released-checkpoint evidence.

Public API

Use the stable configuration, processor, and task-model facades below.

Configuration

SpeechT5Config

View source

SpeechT5Config(**config_kwargs)

Parameters

  • **config_kwargs — Configuration fields validated by SpeechT5Config.

Model

SpeechT5ForTextToSpeech

View source

AutoModelForTextToSpeech.from_pretrained(
    pretrained_model_name_or_path,
    *,
    model_type='speecht5',
    config=None,
    **model_kwargs,
)

Parameters

  • pretrained_model_name_or_path — Hub ID or compatible local directory.
  • model_type — Canonical model type; use 'speecht5'.
  • config — Optional preloaded SpeechT5Config instance.
  • **model_kwargs — Model-specific loading arguments.
from voicehub import get_model_spec

spec = get_model_spec('speecht5')
print(spec.display_name, spec.task.value)
Purpose Public object
Discover get_model_spec('speecht5')
Load and run AutoModelForTextToSpeech
Configure SpeechT5Config
Process AutoProcessor
Model implementation SpeechT5ForTextToSpeech
Normalized output TTSOutput
Training contract get_training_spec('speecht5')
Optimization lifecycle available_optimization_passes, apply_optimization_plan, optimization_manifest, restore_optimization_plan

See all model guides, inference, and the training matrix.