Automatic speech-to-text
Turn every recorded call into accurate, searchable text.
Voice is still where most customer conversations happen — and it is the hardest channel to learn from. Recordings pile up, but almost none get listened to. The insight sits locked inside audio no one has time to review.
Speech-to-text unlocks it. By transcribing calls into accurate text, Feelingstream turns your entire call archive into data you can search, analyse and act on — the foundation every other capability builds on.
Built for real conversations, not studio audio
Generic speech engines are trained on clean, scripted audio. Real customer calls are nothing like that: crosstalk, background noise, dialects, hesitations and domain-specific vocabulary. Our models are trained on spontaneous speech in real phone calls, per language, which is why domain-tuned ASR consistently outperforms one-size-fits-all engines.
We have particular depth in Nordic and Baltic languages — Finnish, Norwegian, Estonian and more — where generic models tend to struggle most.
Speaker-separated, analysis-ready
When agent and customer are recorded on separate channels, each speaker is transcribed independently. That makes it possible to measure who spoke when, detect silence, and assess the agent's contribution on its own — not just a merged transcript.
The foundation for everything else
Once calls are text, they join your chats and emails in one place. That single step is what enables:
- Automatic summaries of every interaction
- Automatic quality scoring across 100% of calls
- Search and concordance over the whole archive
Where to go next
- Pillar guide: What is conversation analytics?
- Related use case: Score every conversation
- Security: Data security
Want to see transcription accuracy on your own calls, in your own language? Book a demo.
Frequently asked questions
- Which languages are supported?
- Feelingstream's ASR is built for multilingual environments, with particular depth in Nordic and Baltic languages such as Finnish, Norwegian and Estonian. Text analysis then works across the languages your customers actually use.
- Why not use a generic speech engine?
- Our models are trained on spontaneous speech in real phone calls, which differs sharply from scripted or studio audio. Domain-tuned models outperform generic ones, especially for smaller Nordic and Baltic languages.
- Do I need calls recorded a particular way?
- Ideally the agent and customer are recorded on separate channels, so each speaker can be transcribed and analysed independently. This improves accuracy and makes speaker-level analysis possible.