![]() ![]() This is particularly useful in the case of noisy audio signals or when uncommon, domain-specific words are present.Īdditional, interesting options are the filter for profanities – which allow to mask profanities with asterisks – and the possibility to receive interim results, i.e., partial results marked as non-final.Ī few clients are provided for common programming languages (e.g., Python, Java, iOS, Node.js), both for batch and real-time requests (with asynchronous responses). In order to improve the accuracy of the system, words or sentences can be attached to the request as text. Supported formats are raw audio and FLAC format, while MP3 and AAC are not accepted. The file to recognise can be provided both by including the audio signal into the HTTP request payload (encoded with Base64) or by giving the URI of the file (currently, only Google Storage can be used). ![]() Optionally, it can be requested to return multiple alternatives in addition to the best-matching, each one with the estimated accuracy. The batch processing is very straightforward just by providing the audio file to process and describing its format the API returns the best-matching text, together with the recognition accuracy. The API, still in alpha, exposes a RESTful interface that can be accessed via common POST HTTP requests. An Outline of the Google Cloud Speech API Now that such technology will be accessible as a cloud service to developers, it will allow any application to integrate speech-to-text recognition, representing a valuable alternative to the common Nuance technology (used by Apple’s Siri and Samsung’s S-Voice, for instance) and challenging other solutions such as the IBM Watson speech-to-text and the Microsoft Bing Speech API. Speech-to-text features are used in a multitude of use cases including voice-controlled smart assistants on mobile devices, home automation, audio transcription, and automatic classification of phone calls. The neural network is updated as new speech samples are collected by Google, so that new terms are learned and the recognition accuracy keeps on increasing. The capability to convert voice to text is based on deep neural networks, state-of-the-art machine learning algorithms recently demonstrated to be particularly effective for pattern detection in video and audio signals. This speech recognition technology has been developed and already used by several Google products for some time, such as the Google search engine where there is the option to make voice search. Google recently opened its brand new Cloud Speech API – announced at the NEXT event in San Francisco – for a limited preview. You can find an example on how to use it here.Discover the Strengths and Weaknesses of Google Cloud Speech API in this Special Report by Cloud Academy’s Roberto Turrin This will be replaced with the Web Speech API, which is a javascript API. The x-webkit-speech input field is being deprecated due to lack of support in other browsers. A user cannot speak multiple languages to a speech recognition system without first requesting it to change to that language. But the speech recognition engine can only support one language/dialect at a timer per user. For example a vendor may support Mexican Spanish, American Spanish and Spain Spanish which all have slightly different dialects. Each vendor has a list of languages it supports and they are specific to a region. ![]() But the caveat is that you have to tell the system what language to use and it has to support the language in question. Windows Speech Recognition supports other languages, as does most speech recognition systems. Update on Answer From Comments on Language Support Nuance is the other big player in the speech recognition market (I believe that is what Siri uses) and they do have solutions that offer speech recognition as a service. Steep learning curve using this solution and if you want it to be setup as a service you will have to develop that yourself. The only other free alternative I can think of is Sphinx which is an open source project out of Carnegie Mellon University. They have some of the top speech scientists working for them. They have a lot of experience with it in other projects like Google Voice and the now defunct Google 411. Google's speech recognition is right up there with a lot of the more popular commercial solutions. If you are accessing it through a Chrome browser using x-webkit-speech on the other hand you are probably safe since it is supported by Google. This recently happened to developers that used the Google Weather API. ![]() If you are planning on accessing the API directly for a commercial product I would not recommend it because they can drop it or change it without warning, breaking your product. Some people have reverse engineered it, as is discussed in this blog. While the Google speech API is free it is not an official public API. ![]()
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