Tech Blog
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2026.08.25Things to know before implementation: the accuracy of Japanese speech recognition
Is the "accuracy rate of X%" for speech recognition truly a reliable indicator? Even a single character error can lead to misrecognition that changes the meaning, potentially having a fatal impact on business operations. This article explains the unique difficulties of the Japanese language and how AmiVoice addresses them through proper noun registration and industry-specific engines.
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2025.12.01What is speech segment detection?
Are you familiar with "voice activity detection", a system that detects only "where a person is speaking"? Not only does it filter out noise and hold music, improving recognition accuracy, but it also has the benefit of "paying only for the time you're speaking". We'll explain in an easy-to-understand way a new perspective on choosing a speech recognition service.
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2025.03.11Prerequisites for developing systems using speech recognition <Part 2> - Development Know-how Series 2 -
From the perspective of a speech recognition system developer, we will explain useful knowledge to know before introducing speech recognition. This time, we will cover the prerequisites for introducing speech recognition (Part XNUMX).
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2025.03.11Prerequisites for developing systems using speech recognition <Part 1> - Development Know-how Series 1 -
When developing a system that uses speech recognition, do you have concerns about recognition accuracy or how to control it so that users can use it effectively? Here are some useful prerequisites to know before developing a speech recognition system.
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2025.01.30How far can dialect speech recognition go? The case of AmiVoice
Even though they are dialects, there are differences in words and phrases, and in intonation and accent. We will explain what and how much AmiVoice recognizes.
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2024.12.18Learn from scratch! How to measure speech recognition accuracy (speech recognition rate)
The developer of AmiVoice will explain in detail how to measure the speech recognition rate, which is used to check how accurately the speech is being recognized. This is useful as an indicator of the performance of a speech recognition engine, and is useful during development and when comparing speech recognition engines.
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2024.01.24How to measure speech recognition accuracy (speech recognition rate) using jiwer
This article explains how to measure speech recognition accuracy using a Python library called jiwer.
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2023.08.30Differences and features between hybrid speech recognition and End-to-End speech recognition
We will explain the differences and features between hybrid speech recognition and end-to-end speech recognition, and also explain the method used by Advanced Media, taking into account the features of each.
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2023.03.06A quick explanation of how speech recognition works!
An engineer involved in research into speech recognition will provide a rough and easy-to-understand explanation of how speech is converted into text, the mechanisms and types of speech recognition, the features of each, and how to choose the appropriate engine.
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2023.01.16A system for transcribing contact center calls using voice recognition (SIP edition)
We will introduce a system that uses voice recognition in contact centers to automatically transcribe calls. This is a method of capturing call audio using the SIP protocol.
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2022.11.29What sampling rate is necessary for speech recognition?
This article explains the optimal sampling rate for speech recognition. It also provides a detailed explanation of how to handle sampling rates with the AmiVoice API.
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2022.05.30What is "orthographic variation" in speech recognition?
In speech recognition, "orthographic variation" can occur between the recognition result and the correct sentence. This article explains what "orthographic variation" is and to what extent it occurs in actual speech recognition.
Most Viewed Articles
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A quick explanation of how speech recognition works!
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Comparing the speech recognition rates of OpenAI's Whisper and AmiVoice for "conference" audio
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How to Choose a Speech Recognition API: 4 Comparison Points to Avoid Mistakes
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Things to know before implementation: the accuracy of Japanese speech recognition
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