Amazon Transcribe 可以自動偵測語言了

Amazon Transcribe 可以將聲音轉成文字,先前都需要自己指定語言,而這幾天發表新的功能,可以自動偵測語言:「Amazon Transcribe Now Supports Automatic Language Identification」。

不過系統要求最少要有 30 秒的資料,跟人類比起來還是有點差距,但比起之前好用不少:

With a minimum of 30 seconds of audio, Amazon Transcribe can efficiently generate transcripts in the spoken language without wasting time and resources on manual tagging.


There is no additional charge on top of the existing pricing.


Amazon Transcribe 增加許多客製化功能

Amazon TranscribeAWS 提供的語音辨識服務,最近發表了不少可以客製化的功能:「Amazon Transcribe enhances custom vocabulary with custom pronunciations and display forms」。

一個是可以增加字彙,包括他的發音 (不過得透過 IPA 標,這邊會需要學一些東西):

You can give Amazon Transcribe more information about how to process speech in your input audio or video file by creating a custom vocabulary. A custom vocabulary is a list of specific words that you want Amazon Transcribe to recognize in your audio input. These are generally domain-specific words and phrases, words that Amazon Transcribe isn't recognizing, or proper nouns.

Now, with the use of characters from the International Phonetic Alphabet (IPA), you can enhance each custom terminology with corresponding custom pronunciations. Alternatively, you can also use the standard orthography of the language to mimic the way that the word or phrase sounds.


Additionally, you can now designate exactly how a customer terminology should be displayed when it is transcribed (e.g. “Street” as “St.” versus “ST”).



2013 年時在「Automatic Translation Without Dictionaries」這邊看到關於機器翻譯時的自我學習方式,裡面提到了「How Google Converted Language Translation Into a Problem of Vector Space Mathematics」這篇報導,而裡面提到的論文則是 Google 發表在 arXiv 上的「Exploiting Similarities among Languages for Machine Translation」這篇。

最近看到「The Illustrated Word2vec」這篇,把五年多前的記錄交叉拉出來看... 這個算式算是給了大家基本的想法,透過公式來解釋文字的意義:

拉出這樣的關係後,就有機會學習新的詞彙... 進而用在其他語言的翻譯上。

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Twitter 上看到 Tor Browser 在宣傳繁體中文版,不過這篇的翻譯有點...:


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其實有不少有趣 (?) 的設計...