Accurate Speech Recognizer
May 26, 2021

Accurate Speech Recognizer

Suresh K.S Kumar | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User

Overall Satisfaction with Nuance Dragon Speech Recognition

Nuance makes speech recognition so easy. I've had experience with other recognition systems, but the recognition from Nuance is accurate even when the confidence of the speaker is sometimes low. Having a multimodal input always provides an option to provide input apart from the traditional DTMF input. It is certainly a more efficient way of communication.
  • Recognition
  • Voice Authentication
  • Speech Transcription
  • Redundancy
  • Latency between listening and recognizing is a pain sometimes.
  • Application Stability
  • Faster Recognition
  • Easy Integration
  • Stable Application
  • Level of installation complexity is high.
  • License sensitive.
  • Accuracy levels are higher.
Nuance Dragon uses recognition models based on the analysis of thousands of voice and text samples when users set and train their user profile. The created user profiles are then modified based on their sound (acoustic model) as well as the words and expressions used (vocabulary and corresponding language model). This synchronization method takes into account users' various accents and speech patterns. Dictation is 3 three times faster when compared to other recognition software.

Do you think Nuance Dragon Speech Recognition delivers good value for the price?

Yes

Are you happy with Nuance Dragon Speech Recognition's feature set?

Yes

Did Nuance Dragon Speech Recognition live up to sales and marketing promises?

No

Did implementation of Nuance Dragon Speech Recognition go as expected?

Yes

Would you buy Nuance Dragon Speech Recognition again?

Yes

The main advantage is that it adjusts to your tone and accent. Integration with a wide range of apps and operating systems is advantageous. It is very simple to incorporate custom words and acronyms, so recognition becomes very precise and customized over time as the system gets trained on the usual utterances. The system might not be perfect when the background noise is included in the input causing recognition to fail.