A speech to text API that converts speech to text. By sending audio to the API endpoint, you receive a transcribed text of the speech. Speech-enabled applications such as for conference transcriptions and voice dialogue systems can be created.
For detailed information on the features,Documentsto check more details.
There are two main approaches: one that processes audio streams and short speeches quickly and converts them to text in real time, and another that processes large audio files in batches.
The Conversation_General-purpose engine is constantly updated to the latest version by the Auto-Training System (ATS). It can also recognize new words that have only recently appeared.
Punctuation and question marks are automatically added to the recognition results, supporting the creation of more accurate and easily understandable spoken language.
You can register words in the user dictionary, such as product names and proper nouns, depending on the usage scenario. This improves the recognition accuracy of specific words and phrases, such as company terminology and names.
Fillers such as "ah," "urm," and "hmm" are automatically deleted (you can also set them not to be deleted). This reduces the effort required to correct recognition results.
You can use it with confidence because inappropriate terms (sexual language, discriminatory language, etc.) in official situations such as business settings will not be converted into text.
The speech recognition results include the estimated spoken forms derived from the speech. These can be used not only for display in applications for children, but also for data matching in downstream systems such as CRM and product databases.
The speech recognition results are assigned a timestamp in milliseconds, with the beginning of the audio data being 0. This makes it possible to obtain the start and end times of each utterance.
This function identifies who spoke and when for audio containing multiple speakers. It identifies and labels speakers without prior training.
It analyzes the speaker's emotions from their voice, outputting 20 parameters such as joy, anger, stress, dissatisfaction, and expectation. This enables detailed voice analysis.
This is a paid option for customers using the AWS environment, providing AWS PrivateLink connectivity to the "AmiVoice API". By creating a VPC endpoint in your Amazon VPC, you can use the speech recognition API from within the AWS network without going through the public internet. You do not need to prepare an internet gateway, NAT Gateway, or public IP address to connect to the speech recognition API. It can be used from systems that prohibit or restrict internet connectivity, simplifying network configuration and potentially reducing associated costs. Synchronous and Asynchronous APIs are separate options. If you use both, fees will be charged for each. If you wish to do so, please notify us through the inquiry form.
The system analyzes the speaker's emotions from the voice and outputs 20 parameters, such as joy, anger, stress, dissatisfaction, and expectation, approximately once every two seconds. It allows for more detailed voice analysis, such as being able to grasp the emotional ups and downs hidden behind the expression "thank you" for example. Sentiment analysis results can be used in a wide range of situations, including contact centers, marketing, human resources, and medicine. We provide ESAS technology. Based on the latest sentiment analysis engine provided by Israel's Nemesysco, it was developed by ES Japan through verification and research of 3 million audio sources in Japan. You can use it with the asynchronous HTTP speech recognition API. You can use it for free for up to 60 minutes per month, so please feel free to try it out.
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