The Word Error Rate (WER) Score is a common metric used for evaluating the performance of speech recognition, machine translation, and transcription systems. It measures the percentage of errors made in transcription, including substitutions, insertions, and deletions, compared to the number of words in the original content. A lower WER indicates higher accuracy.

• Speech Recognition Systems
• Machine Translation Services
• Transcription Services
• Automated Subtitling
• Language Learning Apps
• Chatbots and Voice Assistants
• Automotive Voice Control Systems

Let me give you a more practical example:

Suppose you work in a company that uses a voice-to-text software to take minutes of meetings. For example, a team member speaks into a microphone, and the software writes down everything they say. This can be a huge time-saver! However, if the software makes too many mistakes in transcribing the spoken words, then someone has to spend time correcting them, which defeats the purpose.

This is where the Word Error Rate (WER) score comes in. It’s like a report card for your voice-to-text software. If your software’s WER score is 5%, it means it made mistakes with 5 words out of every 100 words it transcribed.

The lower the WER score is, the fewer mistakes made by the software, and the less time your team spends on corrections. So companies aim to use voice-to-text software with the lowest possible WER.

• Designing LLM apps