Based on the advanced end-to-end speech recognition algorithm, the Multi-language Speech Recognition System is applied to multiple scenarios such as content review, intelligent customer service, voice interaction, subtitle transcription, meeting minutes, etc., involving security, communication, insurance, justice and other industries. It supports users' diversified deployment methods and rich integration interfaces, compatible with multiple software and hardware systems, providing customers with efficient and convenient speech recognition services.
It supports API and multiple SDK access, with good compatibility, and supports Linux, Kylin, x86, arm and other software and hardware systems, meeting the individual needs of users in different business areas.
It provides a custom speech self-training model optimization tool, which does not need any operation of the technicians, and the users can directly upload business data, thus realizing the accurate improvement of the speech recognition effect of personalized scenarios.
Multilingual speech could be recognized, including English, standard Arabic, Arabic dialect in north Africa, Russian, Kazakh, etc.; relying on rich project experience at home and abroad, it achieves high speech recognition accuracy and quick speech conversion rate.
It supports API and multiple SDK access, with good compatibility, and supports Linux, Kylin, x86, arm and other software and hardware systems, meeting the individual needs of users in different business areas.
It provides a custom speech self-training model optimization tool, which does not need any operation of the technicians, and the users can directly upload business data, thus realizing the accurate improvement of the speech recognition effect of personalized scenarios.
Multilingual speech could be recognized, including English, standard Arabic, Arabic dialect in north Africa, Russian, Kazakh, etc.; relying on rich project experience at home and abroad, it achieves high speech recognition accuracy and quick speech conversion rate.
It supports API and multiple SDK access, with good compatibility, and supports Linux, Kylin, x86, arm and other software and hardware systems, meeting the individual needs of users in different business areas.
It provides a custom speech self-training model optimization tool, which does not need any operation of the technicians, and the users can directly upload business data, thus realizing the accurate improvement of the speech recognition effect of personalized scenarios.
Multilingual speech could be recognized, including English, standard Arabic, Arabic dialect in north Africa, Russian, Kazakh, etc.; relying on rich project experience at home and abroad, it achieves high speech recognition accuracy and quick speech conversion rate.
According to the users' personalized demand, it provides speech model self-learning tools, to perform in-depth customization of models such as language and acoustics. The users can upload text or audio data by themselves, thus improving the recognition accuracy of specific business areas.
The technology could be integrated into various Apps, intelligent home appliances, intelligent assistants and other products, recognizing short speech (within one minute) in short speech interaction scenarios, such as voice search, voice command, address book dialing, etc.
The Multi-language Speech Recognition System could convert the audio streams to text in real time from live video, meeting minutes and intelligent voice call, without limiting audio duration, which realizes the functions of intelligent sentence segmentation, real-time presentation and content recording, and greatly improves the user experience.
According to the semantic recognition technology, it supports transferring audio files with several hours into corresponding text content, automatically adding punctuation marks, segmenting sentence, and providing services for daily meeting minutes arrangement, call center quality inspection, audio data entry and other scenarios.
According to the users' personalized demand, it provides speech model self-learning tools, to perform in-depth customization of models such as language and acoustics. The users can upload text or audio data by themselves, thus improving the recognition accuracy of specific business areas.
The technology could be integrated into various Apps, intelligent home appliances, intelligent assistants and other products, recognizing short speech (within one minute) in short speech interaction scenarios, such as voice search, voice command, address book dialing, etc.
The Multi-language Speech Recognition System could convert the audio streams to text in real time from live video, meeting minutes and intelligent voice call, without limiting audio duration, which realizes the functions of intelligent sentence segmentation, real-time presentation and content recording, and greatly improves the user experience.
According to the semantic recognition technology, it supports transferring audio files with several hours into corresponding text content, automatically adding punctuation marks, segmenting sentence, and providing services for daily meeting minutes arrangement, call center quality inspection, audio data entry and other scenarios.
According to the users' personalized demand, it provides speech model self-learning tools, to perform in-depth customization of models such as language and acoustics. The users can upload text or audio data by themselves, thus improving the recognition accuracy of specific business areas.
The technology could be integrated into various Apps, intelligent home appliances, intelligent assistants and other products, recognizing short speech (within one minute) in short speech interaction scenarios, such as voice search, voice command, address book dialing, etc.
The Multi-language Speech Recognition System could convert the audio streams to text in real time from live video, meeting minutes and intelligent voice call, without limiting audio duration, which realizes the functions of intelligent sentence segmentation, real-time presentation and content recording, and greatly improves the user experience.
According to the semantic recognition technology, it supports transferring audio files with several hours into corresponding text content, automatically adding punctuation marks, segmenting sentence, and providing services for daily meeting minutes arrangement, call center quality inspection, audio data entry and other scenarios.
Through the speech recognition system, it accurately transfers massive call audios into texts, providing effective data support for the quality control system establishment in call centers of enterprises, thus improving service standards.
Through speech recognition, meeting minutes information can be efficiently converted, which can improve the speed of storage and arrangement of speech contents, and improve user experience.
It converts foreign language live video into text in real time, and quickly generates subtitles that are highly matched with audio content, helping the audience accurately understand the live content.
Through the speech recognition system, it accurately transfers massive call audios into texts, providing effective data support for the quality control system establishment in call centers of enterprises, thus improving service standards.
Through speech recognition, meeting minutes information can be efficiently converted, which can improve the speed of storage and arrangement of speech contents, and improve user experience.
It converts foreign language live video into text in real time, and quickly generates subtitles that are highly matched with audio content, helping the audience accurately understand the live content.
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