About the service
I build speech recognition and audio processing pipelines that turn raw recordings into accurate, searchable transcripts. The foundation of my work is automatic speech recognition with speaker diarization: each utterance tied to the right speaker, marked with precise word-level timestamps, and returned with restored punctuation and capitalization. Before recognition itself, I clean the signal: noise reduction, reverb removal, volume normalization, and speech detection, because good transcription starts with a clean waveform, not a heavier model. A call, podcast, interview, or hours of video—you get readable text neatly segmented.
On top of basic transcription, I add layers that make audio useful at scale. Keyword and phrase search highlights important moments, language and topic detection correctly routes each file, and summaries and chapter marks make long recordings easy to navigate. I fine-tune acoustic and language models on your vocabulary—product names, medical and legal terms, accents, and code-switching—so accuracy holds on real material, not just clean demos. Everything is measured: I show word error rate, diarization error, and latency on your own samples so you see exactly what you're paying for.
You choose the delivery format. I make streaming or batch API with clear JSON, subtitle files, or a light editing interface where your team corrects and exports transcripts. I deploy on your infrastructure or in the cloud, balancing cost and throughput, and set up monitoring so quality doesn't degrade. You send audio and video—you get structured text with timestamps and speaker labels that you can search, quote, and build on.
— Recognition with diarization, timestamps, and punctuation
— Noise reduction and audio cleanup before recognition
— Keyword search, language detection, and summaries
— API, subtitles, or browser editing interface
On top of basic transcription, I add layers that make audio useful at scale. Keyword and phrase search highlights important moments, language and topic detection correctly routes each file, and summaries and chapter marks make long recordings easy to navigate. I fine-tune acoustic and language models on your vocabulary—product names, medical and legal terms, accents, and code-switching—so accuracy holds on real material, not just clean demos. Everything is measured: I show word error rate, diarization error, and latency on your own samples so you see exactly what you're paying for.
You choose the delivery format. I make streaming or batch API with clear JSON, subtitle files, or a light editing interface where your team corrects and exports transcripts. I deploy on your infrastructure or in the cloud, balancing cost and throughput, and set up monitoring so quality doesn't degrade. You send audio and video—you get structured text with timestamps and speaker labels that you can search, quote, and build on.
— Recognition with diarization, timestamps, and punctuation
— Noise reduction and audio cleanup before recognition
— Keyword search, language detection, and summaries
— API, subtitles, or browser editing interface
