According to AlphaMoat, as of 2026-09, Azure Ai Transcription Py has 3,316 downloads and 2 stars — ranked #3,409 of 5,078 AI skills overall, and #433 of 577 in Development.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 102 | 3.0K | 1 | - |
| SkillHub ↗ | 100 | 3.3K | 2 | — |
Platforms count differently and update at different times.
It supports transcription through Azure and includes capabilities such as timestamps and speaker diarization; the guide provides subscription-key authentication, batch, and real-time streaming examples. Audio content or source URLs are processed by Azure. Confirm authorization to send a recording and protect the subscription key before use.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change. Other skills share this name; figures from before the change are attributed to this one, which currently has the most downloads.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 3.3K | — | 2 |
| 2026-08 | 3.1K | +5.0% | 2 |
| 2026-07 | 2.9K | +9.0% | 2 |
| 2026-06 | 2.7K | +5.7% | 1 |
| 2026-05 | 2.5K | — | 1 |
| 2026-03 | 2.0K | — | 1 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: azure-ai-transcription-py description: | Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient". package: azure-ai-transcription --- # Azure AI Transcription SDK for Python
Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.
## Installation
```bash
pip install azure-ai-transcription
```
## Environment Variables
```bash
TRANSCRIPTION_ENDPOINT=https://<resource>.cognitiveservices.azure.com
TRANSCRIPTION_KEY=<your-key>
```
## Authentication
Use subscription key authentication (DefaultAzureCredential is not supported for this client):
```python
import os
from azure.ai.transcription import TranscriptionClient
client = TranscriptionClient(
endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
credential=os.environ["TRANSCRIPTION_KEY"]
)
```
## Transcription (Batch)
```python
job = client.begin_transcription(
name="meeting-transcription",
locale="en-US",
content_urls=["https://<storage>/audio.wav"],
diarization_enabled=True
)
result = job.result()
print(result.status)
```
## Transcription (Real-time)
```python
stream = client.begin_stream_transcription(locale="en-US")
stream.send_audio_file("audio.wav")
for event in stream:
print(event.text)
```
## Best Practices
1. **Enable diarization** when multiple speakers are present
2. **Use batch transcription** for long files stored in blob storage
3. **Capture timestamps** for subtitle generation
4. **Specify language** to improve recognition accuracy
5. **Handle streaming backpressure** for real-time transcription
6. **Close transcription sessions** when complete
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.