I would like to translate an English word to its phonetic transcription work. Only text convert. Like I have work hello how are you so this will be converted to /ˈheˈləʊ haʊ ə jʊ/. Any one know the API? Any demo link please share with me. .
Try the WikSpeak in sourceforge:
https://sourceforge.net/projects/wikspeak/
WikSpeak is a tool that allows non-native English speakers to analyze the correlation between the pronunciation and spelling of English words. This program is a simple and fast graphic interface which can retrieve the phonetic transcription ( IPA ) and the pronunciation of any English word, while avoiding the annoying process of browsing dictionaries. The most outstanding features of WikSpeak are the savings in time to determine the pronunciation of English words and the ease in understanding phonetic transcription.
WikSpeak is a highly recommended tool for anyone from the beginner to the advanced non-native English speaker.
Related
I noticed that transcribing speech in multiple languages with openai whisper speech-to-text library sometimes accurately recognizes inserts in another language and would provide the expected output, for example: 八十多个人 is the same as 八十几个人. So 多 and 几 are interchangeable and they can both mean several.
Yet, the same audio input on a different pass (with the same model, or a smaller/bigger model) would intermittently result in glitches where the entire sentence is being translated rather than transcribed. I.e. a fragment would be translated either into the first or the second language that appears in the audio. With the example input above either the entire sentence would be in English (with Chinese bits translated to English), or the entire sentence would be in Chinese (with the English bits translated to Chinese). Important: in both cases no input language was specified, and no task type was passed (which implies the default --task transcribe).
The docs for whisper mention translation to English as the only available target language (with the option --task translate in the command line version), but there is no mention of translating to other target languages. Yet the behavior mentioned above indicates that the models are capable of doing translation to other languages too.
The question is if there is a known way to configure the models to do just text-to-text translation? Or is the behavior just some sort of glitch that is not something that can be 'exploited' or configured on a lower level that would allow using the models just for text translation between any of the supported languages?
According to a comment in the whisper's issue tracker this might be a possible answer:
From the paper, the dataset that was used did not use any English audio to polish text samples. The dataset was cleaned by using a different model to match spoken language with text language. If they did not match, the sample was excluded. An exception was made for a portion of the training data to match any spoken language to English text (X->en) translation.
So unfortunately there is no direct way, the model wasn't trained on it. For your use case, this can transcribe to English text, but there has to be some an outside system to translate from English text to Polish text.
The --language parameter is defined in the cli as:
--language
language spoken in the audio, specify None
to perform language detection (default: None)
Yet, despite the help text above this can have potentially useful undocumented side effects.
The 'exploit'
The undocumented glitch that was observed is that if you set a source language e.g. es but the audio input contains English then the English part of the input will be translated to Spanish. Parts of the audio input that are not in English will be transcribed although depending on the language it might not always work or it might generate garbage translations.
So the 'exploit' is that the models can be used to parse English audio and then translate it to a supported language.
The behaviour above occurs with the regular transcribe mode (the default, ie. --task transcribe), and is reproducible with both the original whisper implementation in python, as well as the CPU-optimized C++ port whisper.cpp which is using the same models but apparently with different parameters.
The quality of the non-English translation would depend on the language, and seems to be generally of lower quality that translating from English with the open-source huggingface models (e.g. Helsinki-NLP/opus-mt-es-en, facebook/m2m100_418M, facebook/m2m100_1.2B etc).
We try to use build-in iOS text-to-speech tool for reading Chinese words in the app.
It's good in reading texts. But got problems reading separate words.
For example, we have character 还. It could be pronounced like "hái" with meaning "also, in addition"; and could be pronounced like "huàn" with meaning "to return".
In phrase 我还要还钱 (wǒ hái yào huàn qián) it pronounce 还 in both ways (correct).
In case of separate "还" iOS prefer to read it only like "hái". How to make it pronounce characters in the way we need it (if possible)?
As a quick solution you can cut required words from longer files and play them as audio instead of using TTS
I read a few papers about machine translation but did not understand them well.
The language models (in Google translate) use phonetics and machine learning as best as I can tell.
My question then becomes is it possible to convert an Arabic word that is phonetically spelled in English to translate the users intended Arabic word?
For instance the word 'Hadith' is an English phonetic of the Arabic word 'حديث'. Can I programmatically go from 'Hadith' to Arabic?
Thanks the Wiki article, there's an entire field of work in the area of Transliteration. There was a Google API for this that was deprecated in 2011 and moved to the Google Input Tools service.
The simplest answer is Buck Walter Transliteration but at first glace a 1:1 mapping doesn't seem like a good enough idea.
I am going to try to see if there's a way to hack the Google Input tools and call it even at CLI level because their online demo works very well
I am developing an app that has a text to speech feature. I also let the user to choose want language they want by changing the voice of the AVSpeechUtterance. The language is either American English (en-us) or British English (en-uk).
I tested the app by synthesising
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In the speech, I could clearly hear the -er in "answer". So it was American English. But I actually selected British English!
Then I selected American English and the same, exact voice is produced!
I thought this was because I didn't actually set the voice property to en-uk. So I added some breakpoints and check. It turns out that I did set it to en-uk!
Why is this? Is British English just not available? Or did I entered the locale wrongly? en-uk is not the right one?
Try to use en-gb. According to ISO 3166-1, "UK" is deprecated country code.
I would like to localize my app (as suggested from Apple) to several languages like English, Spanish, French, etc...
Well I don't speak or understand all those languages, at least my translations look awkward to native speakers.
(Results from online translators are a first start but of course insufficient.)
So does anybody know a service/platform where I can get translations from human native speakers mutually.
For example:
I speak German mother tongue and need my app/text/website translated to English.
Some other guy might speak English mother tongue and needs his app/text/website translated to German.
So I could do it for him and he for me. Without paying money, but with high quality, because both have a benefit. Unfortunately I don't have a clue how to find this guy, do you have an idea? Is there a platform on the internet which could help out?
My google research did not get a valuable result.
I would suggest using a professional service, speaking a language does not mean you can do a good translation.
There are a few recommended vendors from apple:
https://developer.apple.com/internationalization/#vendors
I work for Supertext and we also do lots of app translations.