Speech Recognition

The Speech Recognition model enables you to transcribe spoken words into written text and is the foundation of all AssemblyAI products.

On top of the core transcription, you can enable other features and models, such as Speaker Diarization, by adding additional parameters to the same transcription request.

Quickstart

The following example transcribes an audio file from a URL.

Example output

Smoke from hundreds of wildfires in Canada is triggering air quality alerts
throughout the US. Skylines from Maine to Maryland to Minnesota are gray and
smoggy. And...

Word-level timestamps

The response also includes an array with information about each word:

[Word(text='Smoke', start=250, end=650, confidence=0.73033), Word(text='from', start=730, end=1022, confidence=0.99996), ...]

Transcript status

After you've submitted a file for transcription, your transcript has one of the following statuses:

Status	Description
processing	The audio file is being processed.
queued	The audio file is waiting to be processed.
completed	The transcription has completed successfully.
error	An error occurred while processing the audio file.

Handling errors

If the transcription fails, the status of the transcript is error, and the transcript includes an error property explaining what went wrong.

note

A transcription may fail for various reasons:

• Unsupported file format
• Missing audio in file
• Unreachable audio URL

If a transcription fails due to a server error, we recommend that you resubmit the file for transcription to allow another server to process the audio.

Select the speech model with Best and Nano

We use a combination of models to produce your results. You can select the class of models to use in order to make cost-performance tradeoffs best suited for your application. You can visit our for more information on our model tiers.

Name	SDK Parameter	Description
Best (default)	aai.SpeechModel.best	Use our most accurate and capable models with the best results, recommended for most use cases.
Nano	aai.SpeechModel.nano	Use our less accurate, but much lower cost models to produce your results.

You can change the model by setting the speech_model in the transcription config:

For a list of the supported languages for each model, see Supported languages.

Automatic punctuation and casing

By default, the API automatically punctuates the transcription text and formats proper nouns, as well as converts numbers to their written format.

To disable punctuation and text formatting, set punctuate and format_text to False in the transcription config.

Automatic language detection

With automatic language detection, you can identify the dominant language spoken in an audio file and use it during the transcription.

To enable it, set language_detection to True in the transcription config.

note

Automatic language detection supports English, Spanish, French, German, Italian, Portuguese, and Dutch.

To reliably identify the dominant language, the file needs to contain at least 50 seconds of spoken audio.

Set language manually

If you already know the dominant language, you can use the language_code key to specify the language of the speech in your audio file.

To see all supported languages and their codes, see Supported languages.

Custom spelling

Custom Spelling lets you customize how words are spelled or formatted in the transcript.

To use Custom Spelling, pass a dictionary to set_custom_spelling() on the transcription config. Each key-value pair specifies a mapping from a word or phrase to a new spelling or format. The key specifies the new spelling or format, and the corresponding value is the word or phrase you want to replace.

note

The value in the to key is case-sensitive, but the value in the from key isn't. Additionally, the to key must only contain one word, while the from key can contain multiple words.

Custom vocabulary

To improve the transcription accuracy, you can boost certain words or phrases that appear frequently in your audio file.

To boost words or phrases, include the word_boost parameter in the transcription config.

You can also control how much weight to apply to each keyword or phrase. Include boost_param in the transcription config with a value of low, default, or high.

note

Follow formatting guidelines for custom vocabulary to ensure the best results:

• Remove all punctuation except apostrophes.
• Make sure each word is in its spoken form. For example, iphone seven instead of iphone 7.
• Remove spaces between letters in acronyms.

Additionally, the model still accepts words with unique characters such as é, but converts them to their ASCII equivalent.

You can boost a maximum of 1,000 unique keywords and phrases, where each of them can contain up to 6 words.

Dual-channel transcription

If you have a dual-channel audio file with multiple speakers, you can transcribe each of them separately.

To enable it, set dual_channel to true in your transcription config.

note

Dual-channel audio increases the transcription time by approximately 25%.

The response includes an additional utterances key, containing a list of turn-by-turn utterances.

Each utterance contains channel information and is either 1 or 2:

• Channel 1 corresponds to channel 0 in the file (left channel).
• Channel 2 corresponds to channel 1 in the file (right channel).

Additionally, each word in the words array contains the channel identifier.

Export SRT or VTT caption files

You can export completed transcripts in SRT or VTT format, which can be used for subtitles and closed captions in videos.

You can also customize the maximum number of characters per caption by specifying the chars_per_caption parameter.

Export paragraphs and sentences

You can retrieve transcripts that are automatically segmented into paragraphs or sentences, for a more reader-friendly experience.

The text of the transcript is broken down by either paragraphs or sentences, along with additional metadata.

The response is an array of objects, each representing a sentence or a paragraph in the transcript. See the API reference for more info.

Filler words

The following filler words are removed by default:

• "um"
• "uh"
• "hmm"
• "mhm"
• "uh-huh"
• "ah"
• "huh"
• "hm"
• "m"

If you want to keep filler words in the transcript, you can set the disfluencies to true in the transcription config.

Profanity filtering

You can automatically filter out profanity from the transcripts by setting filter_profanity to true in your transcription config.

Any profanity in the returned text will be replaced with asterisks.

note

Profanity filter isn't perfect. Certain words may still be missed or improperly filtered.

Set the start and end of the transcript

If you only want to transcribe a portion of your file, you can set the audio_start_from and the audio_end_at parameters in your transcription config.

Speech threshold

To only transcribe files that contain at least a specified percentage of spoken audio, you can set the speech_threshold parameter. You can pass any value between 0 and 1.

If the percentage of speech in the audio file is below the provided threshold, the value of text is None and the response contains an error message:

Audio speech threshold 0.9461 is below the requested speech threshold value 1.0

Word search

You can search through a completed transcript for a specific set of keywords, which is useful for quickly finding relevant information.

The parameter can be a list of words, numbers, or phrases up to five words.

API reference

Request

Key	Type	Description
audio_url	string	The URL of your media file to transcribe.

Optional parameters

Parameter	Type	Description
punctuate	boolean	Enable Automatic Punctuation, can be true or false.
format_text	boolean	Enable Text Formatting, can be true or false.
language_detection	boolean	Whether Automatic language detection was enabled in the transcription request, either true or false.
language_code	string	The language of your audio file. Possible values are found in Supported languages. The default value is en_us.
custom_spelling	array	Customize how words are spelled and formatted using to and from values.
word_boost	array	A list of custom vocabulary to boost transcription probability for. See Custom vocabulary for more details.
boost_param	string	The weight to apply to words and phrases in the word_boost array; can be "low", "default", or "high".
dual_channel	boolean	Enable Dual-channel transcription, can be true or false.
disfluencies	boolean	Transcribe filler words, like "umm", in your media file; can be true or false.
filter_profanity	boolean	Filter profanity from the transcribed text, can be true or false.
audio_start_from	integer	The point in time, in milliseconds, to begin transcription from in your media file.
audio_end_at	integer	The point in time, in milliseconds, to stop transcribing in your media file.
speech_threshold	float	Defaults to null. Reject audio files that contain less than this fraction of speech. Valid values are in the range [0,1] inclusive.

Response

Key	Type	Description
text	string	The transcript of the audio file.
words	array	An array containing information about each word
words[i].text	string	The text of the i-th word in the transcript
words[i].start	number	The start of when this word is spoken in the audio file, in milliseconds
words[i].end	number	The end of when this word is spoken in the audio file, in milliseconds
words[i].confidence	number	The confidence score for the transcript of the i-th word
words[i].speaker	string	If Speaker Diarization is enabled, the speaker who uttered the i-th word
utterances	array	If Dual-channel trancription or Speaker Diarization is enabled, a list of turn-by-turn utterance objects.

The response also includes the request parameters used to generate the transcript.

Sentences and paragraphs

Use the id of a completed transcript:

The response is an array of objects, each representing a sentence or a paragraph in the transcript. Each object contains the following keys:

Key	Type	Description
text	string	The transcript of the sentence or paragraph.
start	number	The start time in milliseconds.
end	number	The end time in milliseconds.
words	array	An array containing information about each word. It has the fields as the words object in the transcript response.

Troubleshooting

How can I make certain words more likely to be transcribed?

You can include words, phrases, or both in the word_boost parameter. Any term included has its likelihood of being transcribed boosted.

Can I customize how words are spelled by the model?

Yes. The Custom Spelling feature gives you the ability to specify how words are spelled or formatted in the transcript text. For example, Custom Spelling could be used to change the spelling of all instances of the word "Ariana" to "Arianna". It could also be used to change the formatting of "CS 50" to "CS50".

Why am I receiving a "400 Bad Request" error when making an API request?

A "400 Bad Request" error typically indicates that there's a problem with the formatting or content of the API request. Double-check the syntax of your request and ensure that all required parameters are included as described in the API reference. If the issue persists, contact our support team for assistance.