--- name: azure-text-to-speech description: Generate neural narration audio using Azure AI Speech (REST text-to-speech). Use when synthesizing voiceovers or narration in OpenMontage. Optional cloud TTS provider — preferred when AZURE_SPEECH_KEY is configured; the local piper_tts remains the default offline path. Shares one Speech resource with azure_stt. license: MIT compatibility: Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION). metadata: {"openclaw": {"requires": {"env": ["AZURE_SPEECH_KEY", "AZURE_SPEECH_REGION"]}, "primaryEnv": "AZURE_SPEECH_KEY"}} ---

# Azure AI Speech — Text-to-Speech

Generate narration with **Azure neural TTS** — high-quality multilingual voices, SSML prosody control, and express-as styles, served synchronously by the REST `/cognitiveservices/v1` endpoint (no token exchange, Blob storage, or job polling). In OpenMontage this is exposed through the `azure_tts` tool (`capability=tts`, `provider=azure`). It is an **optional cloud TTS provider** — when `AZURE_SPEECH_KEY` is configured, prefer it for high-quality cloud narration. The local `piper_tts` remains the **default offline path** and the fallback when Azure is unavailable; `elevenlabs_tts` remains the choice for voice cloning.

> Docs: [REST text to speech](https://learn.microsoft.com/azure/ai-services/speech-service/rest-text-to-speech) · [Voice gallery](https://speech.microsoft.com/portal/voicegallery)

## Setup

Same Speech resource as `azure_stt` — **one key/region unlocks both directions** (STT and TTS). Create a **Speech** resource in the [Azure portal](https://portal.azure.com); copy the key and region from its **Keys and Endpoint** page.

```bash export AZURE_SPEECH_KEY=your_speech_resource_key export AZURE_SPEECH_REGION=eastus # your resource's region # export AZURE_TTS_ENDPOINT=https://... # optional: full custom TTS host # (the TTS host is https://<region>.tts.speech.microsoft.com — a different # subdomain than the STT endpoint, hence the separate override var) ```

`azure_tts` reports `AVAILABLE` once `AZURE_SPEECH_KEY` plus either `AZURE_SPEECH_REGION` or `AZURE_TTS_ENDPOINT` are set.

## Using it in a pipeline

Route through `tts_selector` as usual (it auto-discovers `azure_tts`), or call the provider tool directly when the user has approved Azure:

```python from tools.tool_registry import registry registry.discover() tts = registry._tools["azure_tts"]

result = tts.execute({ "text": "Every design decision in this dashboard has a reason.", "voice": "andrew", # alias or full Azure short name "rate": "-4%", # slightly slower for narration # "style": "narration-professional", # for voices that support styles "output_path": "projects/my-video/assets/audio/seg_001.mp3", "output_format": "mp3", # or "wav" (48kHz PCM) for mixing }) ```

If `azure_tts` is unavailable (no key) or errors, fall back per its declared chain: `elevenlabs_tts` → `openai_tts` → `piper_tts`.

## Voice selection

Curated shortlist (aliases accepted by the `voice` param):

| Alias | Voice | Character | |-------|-------|-----------| | `andrew` | en-US-AndrewMultilingualNeural | warm, confident, conversational — the default; founder/explainer register | | `brandon` | en-US-BrandonMultilingualNeural | deeper, measured | | `ava` | en-US-AvaMultilingualNeural | confident, bright female | | `guy` | en-US-GuyNeural | authoritative | | `jenny` | en-US-JennyNeural | friendly, clear |

Any valid Azure voice short name may be passed verbatim (e.g. `de-DE-KatjaNeural`); the *Multilingual* voices handle non-English text well — set `locale` to match the text's language for correct SSML.

## Parameters that matter

- **`rate` / `pitch`** — SSML prosody. Narration usually reads best slightly slowed (`"-4%"` to `"-8%"`); leave pitch at `"0%"` unless correcting a voice. - **`style`** — express-as style for voices that support it (`narration-professional`, `calm`, `newscast`). Unsupported styles are silently ignored by Azure, so listen to a sample before batch runs. - **`output_format`** — `mp3` (48kHz/192kbit) for delivery, `wav` (48kHz PCM) when the segment feeds `audio_mixer` for further processing. - Determinism: a fixed voice + SSML re-renders effectively identical audio — safe to regenerate individual segments without re-recording the whole set.

## Cost

Azure neural TTS Standard tier bills roughly **$16 per 1M characters** (~$0.016 per 1k chars; a 150-word narration segment ≈ $0.015). The tool reports per-call `cost_usd` for the cost tracker. See [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) for current rates.

## Limits & tips

- One `execute` call = one narration segment. Generate per script section (the asset stage convention) rather than one giant paragraph — smaller segments align cleanly to scene timings and are cheap to regenerate. - The synchronous endpoint caps a request at 10 minutes of audio — far above any segment OpenMontage generates. - Text is XML-escaped automatically; do not pre-escape or wrap in SSML — pass plain text plus the `rate`/`pitch`/`style` params. - Verify quality: listen to the first generated segment before batch-running a full script (voice/style fit is a creative decision — surface it at the proposal stage per the Decision Communication Contract).

--- name: azure-text-to-speech description: Generate neural narration audio using Azure AI Speech (REST text-to-speech). Use when synthesizing voiceovers or narration in OpenMontage. Optional cloud TTS provider — preferred when AZURE_SPEECH_KEY is configured; the local piper_tts remains the default offline path. Shares one Speech resource with azure_stt. license: MIT compatibility: Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION). metadata: {"openclaw": {"requires": {"env": ["AZURE_SPEECH_KEY", "AZURE_SPEECH_REGION"]}, "primaryEnv": "AZURE_SPEECH_KEY"}} ---

# Azure AI Speech — Text-to-Speech

Generate narration with **Azure neural TTS** — high-quality multilingual voices, SSML prosody control, and express-as styles, served synchronously by the REST `/cognitiveservices/v1` endpoint (no token exchange, Blob storage, or job polling). In OpenMontage this is exposed through the `azure_tts` tool (`capability=tts`, `provider=azure`). It is an **optional cloud TTS provider** — when `AZURE_SPEECH_KEY` is configured, prefer it for high-quality cloud narration. The local `piper_tts` remains the **default offline path** and the fallback when Azure is unavailable; `elevenlabs_tts` remains the choice for voice cloning.

> Docs: [REST text to speech](https://learn.microsoft.com/azure/ai-services/speech-service/rest-text-to-speech) · [Voice gallery](https://speech.microsoft.com/portal/voicegallery)

## Setup

Same Speech resource as `azure_stt` — **one key/region unlocks both directions** (STT and TTS). Create a **Speech** resource in the [Azure portal](https://portal.azure.com); copy the key and region from its **Keys and Endpoint** page.

```bash export AZURE_SPEECH_KEY=your_speech_resource_key export AZURE_SPEECH_REGION=eastus # your resource's region # export AZURE_TTS_ENDPOINT=https://... # optional: full custom TTS host # (the TTS host is https://<region>.tts.speech.microsoft.com — a different # subdomain than the STT endpoint, hence the separate override var) ```

`azure_tts` reports `AVAILABLE` once `AZURE_SPEECH_KEY` plus either `AZURE_SPEECH_REGION` or `AZURE_TTS_ENDPOINT` are set.

## Using it in a pipeline

Route through `tts_selector` as usual (it auto-discovers `azure_tts`), or call the provider tool directly when the user has approved Azure:

```python from tools.tool_registry import registry registry.discover() tts = registry._tools["azure_tts"]

result = tts.execute({ "text": "Every design decision in this dashboard has a reason.", "voice": "andrew", # alias or full Azure short name "rate": "-4%", # slightly slower for narration # "style": "narration-professional", # for voices that support styles "output_path": "projects/my-video/assets/audio/seg_001.mp3", "output_format": "mp3", # or "wav" (48kHz PCM) for mixing }) ```

If `azure_tts` is unavailable (no key) or errors, fall back per its declared chain: `elevenlabs_tts` → `openai_tts` → `piper_tts`.

## Voice selection

Curated shortlist (aliases accepted by the `voice` param):

| Alias | Voice | Character | |-------|-------|-----------| | `andrew` | en-US-AndrewMultilingualNeural | warm, confident, conversational — the default; founder/explainer register | | `brandon` | en-US-BrandonMultilingualNeural | deeper, measured | | `ava` | en-US-AvaMultilingualNeural | confident, bright female | | `guy` | en-US-GuyNeural | authoritative | | `jenny` | en-US-JennyNeural | friendly, clear |

Any valid Azure voice short name may be passed verbatim (e.g. `de-DE-KatjaNeural`); the *Multilingual* voices handle non-English text well — set `locale` to match the text's language for correct SSML.

## Parameters that matter

- **`rate` / `pitch`** — SSML prosody. Narration usually reads best slightly slowed (`"-4%"` to `"-8%"`); leave pitch at `"0%"` unless correcting a voice. - **`style`** — express-as style for voices that support it (`narration-professional`, `calm`, `newscast`). Unsupported styles are silently ignored by Azure, so listen to a sample before batch runs. - **`output_format`** — `mp3` (48kHz/192kbit) for delivery, `wav` (48kHz PCM) when the segment feeds `audio_mixer` for further processing. - Determinism: a fixed voice + SSML re-renders effectively identical audio — safe to regenerate individual segments without re-recording the whole set.

## Cost

Azure neural TTS Standard tier bills roughly **$16 per 1M characters** (~$0.016 per 1k chars; a 150-word narration segment ≈ $0.015). The tool reports per-call `cost_usd` for the cost tracker. See [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) for current rates.

## Limits & tips

- One `execute` call = one narration segment. Generate per script section (the asset stage convention) rather than one giant paragraph — smaller segments align cleanly to scene timings and are cheap to regenerate. - The synchronous endpoint caps a request at 10 minutes of audio — far above any segment OpenMontage generates. - Text is XML-escaped automatically; do not pre-escape or wrap in SSML — pass plain text plus the `rate`/`pitch`/`style` params. - Verify quality: listen to the first generated segment before batch-running a full script (voice/style fit is a creative decision — surface it at the proposal stage per the Decision Communication Contract).

--- name: azure-text-to-speech description: Generate neural narration audio using Azure AI Speech (REST text-to-speech). Use when synthesizing voiceovers or narration in OpenMontage. Optional cloud TTS provider — preferred when AZURE_SPEECH_KEY is configured; the local piper_tts remains the default offline path. Shares one Speech resource with azure_stt. license: MIT compatibility: Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION). metadata: {"openclaw": {"requires": {"env": ["AZURE_SPEECH_KEY", "AZURE_SPEECH_REGION"]}, "primaryEnv": "AZURE_SPEECH_KEY"}} ---

# Azure AI Speech — Text-to-Speech

Generate narration with **Azure neural TTS** — high-quality multilingual voices, SSML prosody control, and express-as styles, served synchronously by the REST `/cognitiveservices/v1` endpoint (no token exchange, Blob storage, or job polling). In OpenMontage this is exposed through the `azure_tts` tool (`capability=tts`, `provider=azure`). It is an **optional cloud TTS provider** — when `AZURE_SPEECH_KEY` is configured, prefer it for high-quality cloud narration. The local `piper_tts` remains the **default offline path** and the fallback when Azure is unavailable; `elevenlabs_tts` remains the choice for voice cloning.

> Docs: [REST text to speech](https://learn.microsoft.com/azure/ai-services/speech-service/rest-text-to-speech) · [Voice gallery](https://speech.microsoft.com/portal/voicegallery)

## Setup

Same Speech resource as `azure_stt` — **one key/region unlocks both directions** (STT and TTS). Create a **Speech** resource in the [Azure portal](https://portal.azure.com); copy the key and region from its **Keys and Endpoint** page.

```bash export AZURE_SPEECH_KEY=your_speech_resource_key export AZURE_SPEECH_REGION=eastus # your resource's region # export AZURE_TTS_ENDPOINT=https://... # optional: full custom TTS host # (the TTS host is https://<region>.tts.speech.microsoft.com — a different # subdomain than the STT endpoint, hence the separate override var) ```

`azure_tts` reports `AVAILABLE` once `AZURE_SPEECH_KEY` plus either `AZURE_SPEECH_REGION` or `AZURE_TTS_ENDPOINT` are set.

## Using it in a pipeline

Route through `tts_selector` as usual (it auto-discovers `azure_tts`), or call the provider tool directly when the user has approved Azure:

```python from tools.tool_registry import registry registry.discover() tts = registry._tools["azure_tts"]

result = tts.execute({ "text": "Every design decision in this dashboard has a reason.", "voice": "andrew", # alias or full Azure short name "rate": "-4%", # slightly slower for narration # "style": "narration-professional", # for voices that support styles "output_path": "projects/my-video/assets/audio/seg_001.mp3", "output_format": "mp3", # or "wav" (48kHz PCM) for mixing }) ```

If `azure_tts` is unavailable (no key) or errors, fall back per its declared chain: `elevenlabs_tts` → `openai_tts` → `piper_tts`.

## Voice selection

Curated shortlist (aliases accepted by the `voice` param):

| Alias | Voice | Character | |-------|-------|-----------| | `andrew` | en-US-AndrewMultilingualNeural | warm, confident, conversational — the default; founder/explainer register | | `brandon` | en-US-BrandonMultilingualNeural | deeper, measured | | `ava` | en-US-AvaMultilingualNeural | confident, bright female | | `guy` | en-US-GuyNeural | authoritative | | `jenny` | en-US-JennyNeural | friendly, clear |

Any valid Azure voice short name may be passed verbatim (e.g. `de-DE-KatjaNeural`); the *Multilingual* voices handle non-English text well — set `locale` to match the text's language for correct SSML.

## Parameters that matter

- **`rate` / `pitch`** — SSML prosody. Narration usually reads best slightly slowed (`"-4%"` to `"-8%"`); leave pitch at `"0%"` unless correcting a voice. - **`style`** — express-as style for voices that support it (`narration-professional`, `calm`, `newscast`). Unsupported styles are silently ignored by Azure, so listen to a sample before batch runs. - **`output_format`** — `mp3` (48kHz/192kbit) for delivery, `wav` (48kHz PCM) when the segment feeds `audio_mixer` for further processing. - Determinism: a fixed voice + SSML re-renders effectively identical audio — safe to regenerate individual segments without re-recording the whole set.

## Cost

Azure neural TTS Standard tier bills roughly **$16 per 1M characters** (~$0.016 per 1k chars; a 150-word narration segment ≈ $0.015). The tool reports per-call `cost_usd` for the cost tracker. See [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) for current rates.

## Limits & tips

- One `execute` call = one narration segment. Generate per script section (the asset stage convention) rather than one giant paragraph — smaller segments align cleanly to scene timings and are cheap to regenerate. - The synchronous endpoint caps a request at 10 minutes of audio — far above any segment OpenMontage generates. - Text is XML-escaped automatically; do not pre-escape or wrap in SSML — pass plain text plus the `rate`/`pitch`/`style` params. - Verify quality: listen to the first generated segment before batch-running a full script (voice/style fit is a creative decision — surface it at the proposal stage per the Decision Communication Contract).

--- name: azure-text-to-speech description: Generate neural narration audio using Azure AI Speech (REST text-to-speech). Use when synthesizing voiceovers or narration in OpenMontage. Optional cloud TTS provider — preferred when AZURE_SPEECH_KEY is configured; the local piper_tts remains the default offline path. Shares one Speech resource with azure_stt. license: MIT compatibility: Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION). metadata: {"openclaw": {"requires": {"env": ["AZURE_SPEECH_KEY", "AZURE_SPEECH_REGION"]}, "primaryEnv": "AZURE_SPEECH_KEY"}} ---

# Azure AI Speech — Text-to-Speech

Generate narration with **Azure neural TTS** — high-quality multilingual voices, SSML prosody control, and express-as styles, served synchronously by the REST `/cognitiveservices/v1` endpoint (no token exchange, Blob storage, or job polling). In OpenMontage this is exposed through the `azure_tts` tool (`capability=tts`, `provider=azure`). It is an **optional cloud TTS provider** — when `AZURE_SPEECH_KEY` is configured, prefer it for high-quality cloud narration. The local `piper_tts` remains the **default offline path** and the fallback when Azure is unavailable; `elevenlabs_tts` remains the choice for voice cloning.

> Docs: [REST text to speech](https://learn.microsoft.com/azure/ai-services/speech-service/rest-text-to-speech) · [Voice gallery](https://speech.microsoft.com/portal/voicegallery)

## Setup

Same Speech resource as `azure_stt` — **one key/region unlocks both directions** (STT and TTS). Create a **Speech** resource in the [Azure portal](https://portal.azure.com); copy the key and region from its **Keys and Endpoint** page.

```bash export AZURE_SPEECH_KEY=your_speech_resource_key export AZURE_SPEECH_REGION=eastus # your resource's region # export AZURE_TTS_ENDPOINT=https://... # optional: full custom TTS host # (the TTS host is https://<region>.tts.speech.microsoft.com — a different # subdomain than the STT endpoint, hence the separate override var) ```

`azure_tts` reports `AVAILABLE` once `AZURE_SPEECH_KEY` plus either `AZURE_SPEECH_REGION` or `AZURE_TTS_ENDPOINT` are set.

## Using it in a pipeline

Route through `tts_selector` as usual (it auto-discovers `azure_tts`), or call the provider tool directly when the user has approved Azure:

```python from tools.tool_registry import registry registry.discover() tts = registry._tools["azure_tts"]

result = tts.execute({ "text": "Every design decision in this dashboard has a reason.", "voice": "andrew", # alias or full Azure short name "rate": "-4%", # slightly slower for narration # "style": "narration-professional", # for voices that support styles "output_path": "projects/my-video/assets/audio/seg_001.mp3", "output_format": "mp3", # or "wav" (48kHz PCM) for mixing }) ```

If `azure_tts` is unavailable (no key) or errors, fall back per its declared chain: `elevenlabs_tts` → `openai_tts` → `piper_tts`.

## Voice selection

Curated shortlist (aliases accepted by the `voice` param):

| Alias | Voice | Character | |-------|-------|-----------| | `andrew` | en-US-AndrewMultilingualNeural | warm, confident, conversational — the default; founder/explainer register | | `brandon` | en-US-BrandonMultilingualNeural | deeper, measured | | `ava` | en-US-AvaMultilingualNeural | confident, bright female | | `guy` | en-US-GuyNeural | authoritative | | `jenny` | en-US-JennyNeural | friendly, clear |

Any valid Azure voice short name may be passed verbatim (e.g. `de-DE-KatjaNeural`); the *Multilingual* voices handle non-English text well — set `locale` to match the text's language for correct SSML.

## Parameters that matter

- **`rate` / `pitch`** — SSML prosody. Narration usually reads best slightly slowed (`"-4%"` to `"-8%"`); leave pitch at `"0%"` unless correcting a voice. - **`style`** — express-as style for voices that support it (`narration-professional`, `calm`, `newscast`). Unsupported styles are silently ignored by Azure, so listen to a sample before batch runs. - **`output_format`** — `mp3` (48kHz/192kbit) for delivery, `wav` (48kHz PCM) when the segment feeds `audio_mixer` for further processing. - Determinism: a fixed voice + SSML re-renders effectively identical audio — safe to regenerate individual segments without re-recording the whole set.

## Cost

Azure neural TTS Standard tier bills roughly **$16 per 1M characters** (~$0.016 per 1k chars; a 150-word narration segment ≈ $0.015). The tool reports per-call `cost_usd` for the cost tracker. See [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) for current rates.

## Limits & tips

- One `execute` call = one narration segment. Generate per script section (the asset stage convention) rather than one giant paragraph — smaller segments align cleanly to scene timings and are cheap to regenerate. - The synchronous endpoint caps a request at 10 minutes of audio — far above any segment OpenMontage generates. - Text is XML-escaped automatically; do not pre-escape or wrap in SSML — pass plain text plus the `rate`/`pitch`/`style` params. - Verify quality: listen to the first generated segment before batch-running a full script (voice/style fit is a creative decision — surface it at the proposal stage per the Decision Communication Contract).