
Just Practical AI Tutorials.
| Platform | Pricing | Only free issues | Publishes | Weekly | |
|---|---|---|---|---|---|
| Issues | 169 | Founded | 4 years ago | Last Issue | 11 days ago |
| Active | |||||

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Meta’s OmniASR is a beautiful starting point for transcribing lower resource languages. It doesn’t capitalise or punctuate but it’s strong where other transcription models completely fail, say on Irish or other similar langua...
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Transcribing overlapping speakers is a long-standing challenge for AI models.
To date, the approach has been to first transcribe as though there is just one speaker, and then identify and separate the speaker transcripts usi...
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Local voice agents have so far been unusable, largely because large language models (LLMs) that can run on your laptop were not strong enough to maintain a sensible conversation. Models like Gemma 4 are beginning to change th...
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Evaluating and training models for medical transcription is notoriously hard because of the privacy aspects involved in gathering data.
There are very few, if any, solid training sets for medical data, or even good datasets...
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There are a ton of text to speech models out there and it’s hard to know what to choose.
I created some tricky text samples for 10 different models (some proprietary, some open source) to synthesize.
And then I compare them...
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