Your browser does not support the audio tag.įrom listening to the predicted sound of the new Translatotron, its human-like accuracy could solve the criticisms that Google’s current translator has received. Here’s a sound clip in Spanish (source language): This is how Google’s AI Translator is predicted to sound like in comparison to Google Translate. The translated content is then computed by a speech recognition system to transcribe the text. BLEU is the algorithm for evaluating the quality of the text. Translatotron’s speech-to-speech capabilities include measuring the BLEU (Bilingual Evaluation Understudy) score. And with this audio, the original speaker’s vocal characteristics will be layered back into the final audio output. The spectrogram will then be converted to an audio wave which is ready to be played. How will Google’s AI Translator sound like?Īs the Translatotron is based on a sequence-to-sequence network, it takes its source from spectrograms (visual representations of sound frequencies) as input and then analyses the spectrograms using a neural vocoder (a voice encoder) which converts output spectrograms to the target language. Related Article: The Future of Drone Technology The Translatotron aims to take translating technology a step further by proving that “a single sequence-to-sequence model can directly translate speech from one language into speech in another language,” as stated in the blog. Detection and handling of words that do not need to be translated.Ability to accurately retain the voice of the original speaker after translation.Ability to avoid compounding errors between recognition and translation.The new system aims to provide several advantages that make the translation process much simpler over the cascaded systems used previously. It intends to create an end-to-end-sequence model for speech-to-text translation. Here’s what you need to know about the TranslatotronĪccording to Google’s blog on the new AI translator, the development of the Translatotron started in 2016. Related Article: Will Tesla's self-driving cars take over ride-hailing apps like Uber? The Translatotron aims to bridge the language gap more efficiently. Implementing the neural network into Google’s translation processes helps the app skip over a few steps like translating audio to text and back again, thus, systematically processing translations at a faster rate.Īlong with a more efficient system, Google’s prototype AI translator can encode speech and preserve the original speaker’s voice. Rearranges and adjusts the text to create a more human-like response.Uses a broader context to help figure out the most relevant translation.Translates sentences as a whole, instead of piece by piece or word by word.Unlike the previous method of translation, the new system: The new system uses a vast artificial neural network to predict the likelihood of a sequence of words in one single integrated model. It is a sequence-to-sequence model that produces direct speech-to-speech translation without having to go through the three-step translation process. ![]() More recently, Google has ventured off to using a neural machine translation. Relate Article: 5G in the UK: Launch Dates, Devices, and Health ConcernsĪ shift to direct speech-to-speech translation Although this three-step process has done very well in many of Google’s speech-to-speech products like Google Translate, its translations were inaccurate and needed improvements. Text-to-speech synthesis (TTS) to generate speech in the target language from the translated textĭuring the translation process, the system gathers data transcripts from the UN and European Parliament, looking for patterns to find the best translation.Machine translation from the transcribed text into a certain language.Automatic speech recognition to transcribe the speech into text.It was a cascade of systems broken into three separate components: When Google’s first translator launched in 2006, the app used statistical machine translation. This app was commonly used for travelling purposes as it can automatically translate unfamiliar signs and instructions into the user’s known language. ![]() ![]() And Google’s response? Develop a new system: Google’s AI translator dubbed the Translatotron.īefore getting to know the Translatotron, here’s a quick breakdown on what has led to its development.Ī departure from speech-to-text to text-to-speech conversionīefore Google’s AI translator came into the picture, the Google Translate app has been the go-to tool to fill the language gap for years. Although Google Translate has helped bridge language barriers for years, it still received more than enough criticism due to its inaccurate translations.
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