Tts Voiceover
MicrosoftOfficialPublished by Microsoft
- Skill
- Tool integration
- Automation and integrations
- MIT
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill automates the creation of synthetic voice-over audio for slide presentations. It processes speaker notes defined in YAML files, applies custom acronym pronunciations via an SSML-based lexicon, and utilizes Azure AI Speech neural voices to generate individual WAV files for each slide. The tool supports both key-based and Microsoft Entra ID authentication and includes a dry-run mode for verifying SSML templates without incurring synthesis costs.
What it does
- Extracts speaker notes from YAML files within a structured directory.
- Generates WAV audio files using Azure AI Speech neural voices.
- Applies custom pronunciation aliases for acronyms and technical terms.
- Supports SSML template verification through a dry-run mode.
- Allows configuration of speech rate and specific voice selection.
- Enables targeted synthesis for individual slides or entire decks.
When to use it
- When you need to generate consistent synthetic narration for slide-based presentations.
- When you require precise control over the pronunciation of technical acronyms in audio.
- When integrating automated voice-over generation into a slide content pipeline.
- When you need to verify SSML output before committing to full audio synthesis.
Advantages
- Automates the conversion of text-based speaker notes into audio assets.
- Provides granular control over pronunciation using custom lexicon files.
- Supports secure authentication via Microsoft Entra ID.
- Offers flexibility to re-synthesize specific slides without processing the entire deck.
Usage examples
- “Generate voice-over files for all slides in the content directory.”
- The script processes all slide-NNN folders in the content directory and outputs corresponding WAV files to the voice-over folder.
- “Verify the SSML templates for my slides without generating audio.”
- The tool runs in dry-run mode, printing the generated SSML to the console for review without calling the Azure Speech service.
- “Synthesize audio for slide 005 using a specific voice and rate.”
- The tool generates a WAV file for slide-005 using the specified Azure neural voice and prosody rate settings.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/tts-voiceover/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip tts-voiceover.zip -d .agents/skills
Documentation by Microsoft
TTS Voice Over Skill
Generates per-slide WAV voice-over files from YAML speaker_notes using Azure AI Speech neural voices with SSML pronunciation control.
Overview
This skill reads content.yaml files from a slide content directory (slide-NNN/content.yaml), extracts speaker_notes fields, applies acronym aliases for correct pronunciation of technical terms, and produces one WAV file per slide. Supports dry-run mode for SSML template verification without Azure credentials.
Synthesis uses Azure AI Speech neural voices, including the HD voices such as en-US-Andrew:DragonHDLatestNeural. HD voices are offered in a subset of Azure regions; check the Speech service regions before choosing SPEECH_REGION.
Narration produced by this skill is synthetic. Tell listeners that the voice is AI-generated, following Microsoft's disclosure design guidelines for synthetic voices. HVE demo-material CI does not synthesize speech; it generates silent videos.
Prerequisites
Azure Speech resource: see Azure AI Speech pricing for the free-tier allowance and HD voice rates.
Authentication: Microsoft Entra ID (
SPEECH_RESOURCE_ID, recommended) or a resource key (SPEECH_KEY).Region:
SPEECH_REGIONis required for synthesis and has no default. Dry-run mode does not need it.Python 3.11+ with
uvfor virtual environment management.Data handling note: Speaker-notes content is transmitted to the configured
SPEECH_REGIONfor synthesis. For prebuilt neural voices, Microsoft states that neither the input text nor the output audio is stored in Microsoft logs; see Data, privacy, and security for text to speech. Operators must still set an approved region and avoid sending regulated or confidential narration.
Microsoft Entra ID Auth (Recommended)
Entra ID avoids storing a long-lived key. It requires a custom domain on the Speech resource and the Cognitive Services Speech User role for the signed-in identity. The script resolves the identity through DefaultAzureCredential, so an az login session, a managed identity, or a GitHub Actions OIDC login through azure/login all work.
export SPEECH_RESOURCE_ID="/subscriptions/.../Microsoft.CognitiveServices/accounts/your-resource"
export SPEECH_REGION="eastus"Key-Based Auth
export SPEECH_KEY="your-speech-key"
export SPEECH_REGION="eastus"When both SPEECH_KEY and SPEECH_RESOURCE_ID are set, the script warns and uses the key. Unset SPEECH_KEY to use Entra ID.
Install dependencies:
# run from this skill folder
uv syncQuick Start
Verify SSML templates without generating audio:
uv run scripts/generate_voiceover.py --dry-run --content-dir path/to/contentGenerate voice-over WAV files:
uv run scripts/generate_voiceover.py --content-dir path/to/content --output-dir voice-overUse demo-video to combine the WAV files with approved frames or clips.
Use hve-slides for HTML presentations and hve-demo-material for the
HTML/frame/MP4/caption workflow. Audio embedding into presentation files is retired.
Parameters Reference
For different speakers, synthesize one voice's selected slides per invocation
using repeated --slide <number> arguments. Only those canonical slide-NNN
folders are read and their WAVs replaced; other speakers' outputs are untouched.
Omit --slide to synthesize the whole deck.
generate_voiceover.py
| Parameter | Type | Default | Description |
|---|---|---|---|
--dry-run | flag | false | Print SSML without generating audio |
--voice | string | en-US-Andrew:DragonHDLatestNeural | Azure AI Speech voice name |
--rate | string | +10% | Speech prosody rate |
--content-dir | path | content | Path to slide content directory |
--output-dir | path | voice-over | Path to WAV output directory |
--slide | integer | all slides | Repeat to synthesize only the selected canonical slide numbers |
--lexicon | path | (auto-detect) | Custom acronyms.yaml path |
--collapse-newlines | flag | false | Collapse newlines and whitespace runs in speaker notes into single spaces before synthesis |
--verbose / -v | flag | false | Enable verbose (DEBUG) logging output |
Script Reference
Generate with custom voice and rate:
uv run scripts/generate_voiceover.py \
--content-dir content \
--output-dir voice-over \
--voice "en-US-Jenny:DragonHDLatestNeural" \
--rate "+5%"Use a custom lexicon:
uv run scripts/generate_voiceover.py \
--content-dir content \
--lexicon custom-acronyms.yamlCollapse newlines in speaker notes (recommended for block-scalar | notes,
whose line breaks are otherwise spoken as pauses):
uv run scripts/generate_voiceover.py \
--content-dir content \
--collapse-newlinesAcronym Lexicon
The lexicon controls SSML <sub alias> replacements for acronyms and technical terms. Create an acronyms.yaml file:
acronyms:
HVE-Core: "H V E Core"
OWASP: "Oh wasp"
SBOM: "S Bomb"
SLSA: "Salsa"
CI/CD: "C I C D"Lexicon resolution order:
Path specified via
--lexiconargument.acronyms.yamlin the content directory.Built-in defaults covering common technical acronyms.
SSML Template
Each slide produces an SSML document:
<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis"
xmlns:mstts="http://www.w3.org/2001/mstts" xml:lang="en-US">
<voice name="en-US-Andrew:DragonHDLatestNeural">
<prosody rate="+10%">
Text with <sub alias="Oh wasp">OWASP</sub> aliases applied.
</prosody>
</voice>
</speak>Content Directory Contract
This skill reads a slide content directory with this structure:
content/
├── slide-001/
│ └── content.yaml # Must include speaker_notes: field
├── slide-002/
│ └── content.yaml
└── ...Each content.yaml should contain a speaker_notes: field with the narration text. The generated WAV files are named slide-NNN.wav matching the directory names.
Troubleshooting
| Issue | Solution |
|---|---|
Set SPEECH_KEY ... or SPEECH_RESOURCE_ID | Export SPEECH_KEY (key auth) or SPEECH_RESOURCE_ID (Entra ID) with SPEECH_REGION. |
SPEECH_REGION must be set | Export SPEECH_REGION with an approved Azure region. Synthesis has no default region. |
| 401 with Entra ID auth | Verify custom domain on the Speech resource and Cognitive Services Speech User role. RBAC propagation takes up to 5 minutes. |
| Empty WAV files or skipped slides | Verify speaker_notes: is present and non-empty in content.yaml. |
| Mispronounced acronyms | Add entries to acronyms.yaml with phonetic aliases. |
azure-cognitiveservices-speech package is required | Run uv sync in the skill directory. |
Files
- ATTRIBUTION.mdAdded by AutoGineer874 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SECURITY.md20.1 KiB
- SKILL.md9.0 KiB
- pip-audit-known-vulnerabilities.txt260 B
- pyproject.toml1.6 KiB
- scripts/Invoke-GenerateVoiceover.ps1Script4.3 KiB
- scripts/Modules/TtsVoiceoverHelpers.psm1Script2.1 KiB
- scripts/generate-voiceover.shScript2.8 KiB
- scripts/generate_voiceover.pyScript16.8 KiB
- tests/Invoke-GenerateVoiceover.Tests.ps1Script2.3 KiB
- tests/TtsVoiceoverHelpers.Tests.ps1Script4.9 KiB
- tests/conftest.pyScript7.2 KiB
- tests/corpus/0_acronym_text19 B
- tests/corpus/0_empty0 B
- tests/corpus/0_ssml_fragment29 B
- tests/corpus/0_valid_yaml25 B
- tests/fuzz_harness.pyScript6.0 KiB
- tests/test_generate_voiceover.pyScript10.5 KiB
- tests/test_generate_voiceover_boundaries.pyScript9.1 KiB
- uv.lock144.1 KiB
scripts/generate-voiceover.sh
#!/usr/bin/env bash
# Copyright (c) 2026 Microsoft Corporation. All rights reserved.
# SPDX-License-Identifier: MIT
#
# generate-voiceover.sh
# Wrapper for generate_voiceover.py — generates per-slide TTS voice-over
# from YAML speaker notes via Azure Speech SDK.
#
# Required Environment Variables (key-based auth):
# SPEECH_KEY - Azure Speech resource key
# SPEECH_REGION - Azure region (e.g., eastus); required for synthesis
#
# Required Environment Variables (Entra ID auth):
# SPEECH_RESOURCE_ID - Cognitive Services resource ID
# SPEECH_REGION - Azure region; required for synthesis
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
SKILL_ROOT="$(dirname "${SCRIPT_DIR}")"
err() {
printf "ERROR: %s\n" "$1" >&2
exit 1
}
usage() {
cat <<EOF
Usage: $(basename "$0") [OPTIONS]
Generates per-slide WAV voice-over files from YAML speaker notes.
Options:
--dry-run Print SSML templates without generating audio
--voice <name> Azure TTS voice name (default: en-US-Andrew:DragonHDLatestNeural)
--rate <rate> Speech prosody rate (default: +10%)
--content-dir <path> Path to slide content directory (default: content)
--output-dir <path> Path to WAV output directory (default: voice-over)
--lexicon <path> Path to custom acronyms.yaml lexicon file
--collapse-newlines Collapse newlines and whitespace runs in speaker notes
-v, --verbose Enable verbose (DEBUG) logging output
--skip-venv-setup Skip virtual environment setup
-h, --help Show this help message
EOF
exit 0
}
test_uv_availability() {
if ! command -v uv &>/dev/null; then
err "uv is required but was not found on PATH. Install a checksum-verified release: winget install --id astral-sh.uv -e, brew install uv, or an archive from https://github.com/astral-sh/uv/releases checked against its .sha256 file."
fi
}
initialize_python_environment() {
echo "Syncing Python environment via uv..."
uv sync --directory "${SKILL_ROOT}"
echo "Environment synchronized."
}
get_venv_python_path() {
echo "${SKILL_ROOT}/.venv/bin/python"
}
main() {
local -a passthrough_args=()
local skip_venv_setup=false
while [[ $# -gt 0 ]]; do
case "$1" in
-h|--help) usage ;;
--skip-venv-setup) skip_venv_setup=true; shift ;;
*) passthrough_args+=("$1"); shift ;;
esac
done
test_uv_availability
if [[ "${skip_venv_setup}" == "false" ]]; then
initialize_python_environment
fi
local python
python="$(get_venv_python_path)"
if [[ ! -x "${python}" ]]; then
err "Python not found at ${python}. Run without --skip-venv-setup to initialize."
fi
"${python}" "${SCRIPT_DIR}/generate_voiceover.py" "${passthrough_args[@]}"
}
main "$@"
Requirements and compatibility
Written for: GitHub Copilot
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python
Security
What our scanner noticed· Low risk
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/hve-core · .github/skills/experimental/tts-voiceover · commit f425e94
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download tts-voiceover.zip