We recently wrapped up developing our own Finnish speech-to-text model and now it’s ready! Finnish speech-to-text is designed to help large companies detect business critical patterns from customer interactions such as sales leads, efficiency problems, unhappy and leaving customers and customer service quality.
Analysing customer calls helps sales managers find new sales leads (upsell and win-back leads) from existing conversations in near real-time while also providing customer service managers with a tool to help improve customer service quality.
Transcribing customer phone calls into text is the first important step towards finding business critical customer insight. After that, all calls become searchable in Feelingstream. Our AI-based models automatically detect each call’s sentiment, topic etc. This step spawns actionability which could mean contacting clients, improving services, taking advantage of sales opportunities, etc.
There are a couple of reasons why we developed our own Finnish speech-to-text model instead of using cloud-based services:
- Higher accuracy. Our speech-to-text (or ASR – Automatic Speech Recognition) model is more accurate because it is focused on customer conversations in Finnish in specific sectors. This was kept in mind while collecting training data for the model.
- Adaptability. Our speech-to-text model is easily adaptable to customer-specific words. For example, if the model doesn’t recognize specific product names, the model could easily be fine-tuned to increase accuracy.
- On-premises. Our speech-to-text model can be used on-premise without any external connections. This means that you have full control over your data security.
If you are interested in detecting business critical patterns in customer conversations in Finnish, get in touch to see a live virtual demo.