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AI Tool 4 Min Read Dec 14, 2022
Eight interesting speech-to-speech translation tools in 2022
Published By : Dr Nivash Jeevanandam
Speak-to-speech (S2S) translation technologies have been created during the past few decades to facilitate interaction between persons who speak various languages. S2S technology is monumental because it facilitates communication between people who speak different languages worldwide. Moreover, it eliminates a significant barrier to international trade and understanding between people of different cultures. Therefore, it has been predicted that speech-to-speech translation will be one of the top 10 technologies to alter society significantly.
Therefore, a selection of attractive S2S translation models is provided below.
On iOS and Android smartphones, ITranslate Voice provides instant text-to-speech and voice-to-voice translation. It supports 44 languages and dialects, although not equally. Yet, according to some reports, its speech input and output capabilities surpass those of Google Translate. Moreover, AirTranslate is one of its capabilities that can translate dialogue between two iOS devices on the go, making it worthwhile to attempt.
TripLingo is an application for travellers that combines an interactive phrasebook with a direct voice translation and additional travel and language study resources. It provides immediate voice translation in 42 languages, with formal, informal, and slang alternatives for frequent words.
Over 500 million people in China utilise iFlytek Input to overcome barriers in multilingual communications or to communicate with speakers of other Chinese dialects. The software was created by iFlytek, a prominent Chinese AI startup that employs deep learning in various domains, including speech recognition, natural language processing, and machine translation. It was named one of the "50 Smartest Companies of 2017."
Verbmobil is a speaker-independent, bidirectional S2S translation system. It is used to translate spontaneous dialogues in mobile situations. It begins by recognising the input and then conducts additional analysis and translation before producing the final translation. It is a multilingual system that controls the delivery of dialogues in three business-oriented sectors using context-sensitive translation between German, English, and Japanese.
SayHi provides instant speech-to-speech translation for the iPhone and Kindle in 90 languages and dialects (including numerous Arabic dialects). The software boasts a voice recognition accuracy of 95%. In addition, the app allows users to configure the voice to be male or female and to regulate its speed.
The Korean app specialises in English, Korean, Simplified Mandarin, Chinese, and Japanese translation. In addition, the application can perform real-time speech translation and translate conversations, photos, and text. In addition to allowing users to choose between two different images to set the proper context, some helpful features include discussion and offline modes.
Microsoft Translator is a service we can use for personal or professional needs. It offers a cloud-based REST API for speech translations that we may use to construct language translation capabilities for websites and mobile applications. The default translation technique for the Microsoft Translator API is Neural Machine Translation. Formerly known as Microsoft Translator, Bing Translator is an online text translation service.
Skype Translator, which utilises Microsoft's Statistical Machine Translation engine, provides a mobile and desktop application for end-to-end speech-to-speech translation. In addition, Skype translator translates direct text messages into over 70 languages in real-time.
Google Translate is the most accessible online text translator to use. Initially, the network utilised Statistical Machine Translation (SMT) to translate text pairings drawn from United Nations and European Parliament papers and transcripts. However, it could not implement grammar since SMT used predictive translation. Finally, researchers developed a model system for neural machine translation (NMT) at the sentence level.
Google Translate currently supports 109 different languages. The translation procedure consists of three steps. First, the network model identifies language patterns through millions of pages. Despite several language-specific criticisms, Google Translate is the finest translation model. This project also utilises the free Python translation tool Google Translate API.
