Voice AI

Voice AI uses speech recognition and natural language processing to enable human-like interactions with technology. We cover speech-to-text software, including benchmarks of leading tools, and explore the latest applications in the field.

Top AI Note Takers Tested: Motion, Fellow, Otter, and TL;DV

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We tested each AI note taker to evaluate their accuracy and features during real world meetings. Follow the links to view our detailed reviews: AI note taker benchmark results Methodology for evaluating AI note taking tools: We tested AI note takers during a strategy session focused on improving sales in the rural market. 1.

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Top 7 Speech Recognition Challenges & Solutions

Speech recognition technology has significantly advanced in areas like generative AI, voice biometrics, customer service, and smart home devices. Despite rapid adoption, implementing this technology still poses various challenges. Here, we outline the top 7 challenges and best practices for overcoming them: 1.

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Speech-to-Speech Software

Speech-to-speech (S2ST) software is changing the way we communicate. It enables real-time translation and makes conversations easier to follow. This technology helps businesses connect across languages more naturally. Here are the leading speech-to-speech software, you can follow the links to learn their pros & cons.

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Speech Recognition: Everything You Need to Know

Speech recognition, also known as automatic speech recognition (ASR), enables seamless communication between humans and machines. This technology empowers organizations to transform human speech into written text. Speech recognition technology can revolutionize many business applications, including customer service, healthcare, finance and sales.

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Top 11 Voice Recognition Applications & Examples

If you’ve used virtual assistants like Alexa, Cortana, or Siri, you’re likely familiar with speech recognition and conversational AI. This technology enables users to interact with devices through verbal commands by converting spoken queries into machine-readable text. The number of voice assistant users in the U.S.

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Speech-to-Text Benchmark: Deepgram vs. Whisper

We benchmarked the leading speech-to-text (STT) providers, focusing specifically on healthcare applications. Our benchmark used real-world examples to assess transcription accuracy in medical contexts, where precision is crucial. Benchmark results The average WER results of our tasks show that Deepgram is the leading speech-to-text provider for healthcare in this benchmark.