In Summary, ASR allows enterprise brands extract valuable data from unstructured conversations and turn it into structured data to inform better business decisions and insights.
Raw Audio > Transcript > Insights & Analytics
Q: What Are the Use Cases of ASR?
Enterprise businesses can leverage custom-trained ASR speech analytics engines to develop valuable reporting and analytics capabilities to better understand customer and market insights.
Some of the top use cases for enterprise brands include:
- Optimizing Customer Experience in the Contact Center
- Scoring, and tagging calls with automated software
- Tracking Conversions and enabling sales reps with learnings
- Measuring operational performance and cost
- Understand key consumer insights
- Track and measure market insights
- Lower contact center costs
- Custom applications
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Q: What is Automatic Speech Recognition?
Automatic Speech Recognition (ASR) is a type of technology that converts spoken words into text. It’s the first step in transforming spoken audio conversations into valuable data for in-depth analysis and decision making.
Q: How Does ASR Work?
ASR allows computers to detect patterns in audio waveforms and match them with sounds in a specific language, identifying which words were spoken. Simple systems only recognize a small “dictionary” of terms, whereas complex, machine-learning models like those used by VoiceBase can understand millions of spoken words, tone, pitch, emotional context, and other metrics of a conversation.
Q: What is the underlying technology?
Much of ASR involves Natural Language Processing, or NLP. Natural Language Processing ASR essentially enable us to have “conversations” with computers.