Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Text-to-speech voice-over generation from YAML speaker notes using Azure Speech SDK with SSML pronunciation control, or an offline Piper engine that needs no credentials
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Generates per-slide WAV voice-over files from YAML speaker_notes using Azure Speech SDK with SSML pronunciation control, or a locally installed Piper engine.
This skill reads content.yaml files from a PowerPoint skill content directory, 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.
Two engines are available through --engine:
azure (default) sends SSML to Azure AI Speech neural voices. Use it for published narration.piper is an explicit optional local choice using a separately installed Piper executable. It needs no credentials or network access after the voice is downloaded. Narration never leaves the host. HVE demo-material CI does not use either speech engine; it generates silent videos instead.SPEECH_KEY) or Microsoft Entra ID (SPEECH_RESOURCE_ID).SPEECH_REGION is required for Azure synthesis and has no default. Dry-run mode and the piper engine do not need it.uv for virtual environment management.SPEECH_REGION for synthesis. Operators must set an approved region and avoid sending regulated or confidential narration.export SPEECH_KEY="your-speech-key"
export SPEECH_REGION="eastus"
Requires a custom domain on the Speech resource and Cognitive Services Speech User role.
export SPEECH_RESOURCE_ID="/subscriptions/.../Microsoft.CognitiveServices/accounts/your-resource"
export SPEECH_REGION="eastus"
Install dependencies:
# run from this skill folder
uv sync
Piper is not a dependency of this skill. It is licensed GPL-3.0-or-later, so the skill invokes it as an external executable, the same way other skills invoke FFmpeg or LibreOffice. Install it and download a voice separately:
uv tool install piper-tts
uvx --from piper-tts python -m piper.download_voices en_US-norman-medium --data-dir ~/.local/share/piper
export PIPER_DATA_DIR=~/.local/share/piper
To run Piper without installing it, also set:
export PIPER_COMMAND="uvx --from piper-tts piper"
| Variable | Purpose |
|---|---|
PIPER_COMMAND | Command that runs Piper, split without a shell (default: piper) |
PIPER_DATA_DIR | Directory holding downloaded voices; --piper-data-dir takes precedence |
Voice models carry their own licenses and dataset provenance in each voice's
MODEL_CARD. The default en_US-norman-medium model
card
records that it was trained from scratch on public-domain LibriVox recordings,
and the Piper voices repository is MIT licensed. Check the model card before
publishing narration from any other voice, because some voices have
noncommercial or research-only source restrictions.
Verify SSML templates without generating audio:
uv run scripts/generate_voiceover.py --dry-run --content-dir path/to/content
Generate voice-over WAV files:
uv run scripts/generate_voiceover.py --content-dir path/to/content --output-dir voice-over
Generate voice-over offline with Piper:
uv run scripts/generate_voiceover.py --engine piper --collapse-newlines \
--content-dir path/to/content --output-dir voice-over
Embed audio into a PPTX deck:
uv run scripts/embed_audio.py --input deck.pptx --audio-dir voice-over --output deck-narrated.pptx
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.
| Parameter | Type | Default | Description |
|---|---|---|---|
--dry-run | flag | false | Print SSML (azure) or plain text (piper) without generating audio |
--engine | string | azure | Synthesis engine: azure or piper |
--voice | string | en-US-Andrew:DragonHDLatestNeural | Voice name; the piper default is en_US-norman-medium |
--rate | string | +10% | Azure speech prosody rate; ignored by piper |
--piper-data-dir | path | PIPER_DATA_DIR | Directory holding downloaded Piper voices |
--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 |
Embeds WAV files into corresponding PPTX slides and adds narration timing XML so PowerPoint recognizes the audio for video export via File > Export > Create a Video > Use Recorded Timings and Narrations.
| Parameter | Type | Default | Description |
|---|---|---|---|
--input | path | (required) | Source PPTX file path |
--audio-dir | path | voice-over | Directory with slide-NNN.wav |
--output | path | *-narrated.pptx | Output PPTX file path |
--verbose / -v | flag | false | Enable verbose (DEBUG) logging output |
Each WAV file maps to a slide by the number in its name, so slide-1.wav and slide-001.wav both map to slide 1. When two files map to the same slide, embedding stops with an error and writes no output. WAV files numbered past the last slide are ignored with a warning. An unreadable WAV file is reported, its slide is left unchanged, and the remaining slides are still embedded.
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.yaml
Collapse 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-newlines
Embed generated audio:
uv run scripts/embed_audio.py \
--input slide-deck/presentation.pptx \
--audio-dir voice-over \
--output slide-deck/presentation-narrated.pptx
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:
--lexicon argument.acronyms.yaml in the content directory.The piper engine has no SSML support, so it substitutes aliases directly into the text. Aliases written as spaced single letters are hyphenated first (H V E Core becomes H-V-E Core), because Piper reads hyphenated letters as one fluent run and spaced letters as slow separate words.
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>
This skill reads from the PowerPoint skill's content directory 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.
| 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. |
Multiple WAV files map to slide N | Remove the duplicate WAV files (for example slide-1.wav beside slide-001.wav) and rerun embed_audio.py. |
| 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. |
Piper executable not found | Install Piper separately or set PIPER_COMMAND, for example uvx --from piper-tts piper. |
| Piper cannot find the voice model | Download the voice with piper.download_voices and pass its directory through --piper-data-dir or PIPER_DATA_DIR. |
| Audio icon visible in PPTX | Reposition or resize the audio object in PowerPoint after embedding. |
| Authored slide animations missing after embedding | embed_audio.py replaces existing p:timing with narration timing; re-apply animations in PowerPoint after embedding audio. |
| Slides no longer advance on click after embedding | embed_audio.py sets advClick="0" for auto-advance. To re-enable, select all slides in PowerPoint and check Advance Slide > On Mouse Click in the Transitions tab. |
| Video export shows "No timings recorded" | Re-embed audio with the updated embed_audio.py which adds narration timing XML automatically. |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Build, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.
日本語の概要は準備中です。原文の説明を表示しています。
Authoring skill for Architecture Decision Records (ADRs) supporting capture, from-planner-handoff, and adopt-template entry modes with selectable Y-Statement or MADR v4.0.0 output templates, supersession lineage, and ASR trigger evaluation.
日本語の概要は準備中です。原文の説明を表示しています。
Authoring conventions for exploratory data analysis notebooks and analytical dashboards, covering section sequence, visualization selection, scale thresholds, caching and state, and dashboard validation budgets. Use when composing or reviewing an EDA notebook, an analytical dashboard, or a dashboard test pass.
日本語の概要は準備中です。原文の説明を表示しています。
Architecture diagram authoring for cloud infrastructure and declared data catalogs. Use when rendering Azure IaC or DS_CATALOG_V1 relationships as caller-selected ASCII or Mermaid diagrams.
日本語の概要は準備中です。原文の説明を表示しています。
Create a durable Architecture Review Record from a confirmed System Architecture Reviewer scope, evidence, pillar analysis, trade-offs, and dispositions
日本語の概要は準備中です。原文の説明を表示しています。