speechtotext.model.amazonWrapper.AmazonAPIWrapper

class AmazonAPIWrapper(model_version)

Bases: ModelWrapper

Wrapper for AMAZON API. AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AMAZON_REGION and AMAZON_BUCKET need to be in the ‘.env’ file in current directory.

Wrapper for AMAZON model.

Parameters:

model_version (AmazonAPIVersion) – Model version of AMAZON STT API to use.

Methods

benchmark_n_samples	Benchmark n samples with model.
benchmark_sample	Benchmark sample with model.
benchmark_samples	Benchmark samples with model.
convert_sample	Convert sample to correct format.
get_model	Get model.
get_transcript_of_file

Attributes

BUCKET_EXIST	Boolean that represents if the bucket exists.
LANGUAGE_CODE	Code for the language to transcribe.
PATH_OF_TEMP_CONVERTED_AUDIO_FILE	path to temp file that will be created to convert the audio files to an accepted audio format.

BUCKET_EXIST: bool = True

Boolean that represents if the bucket exists.

Type:

bool

LANGUAGE_CODE: str = 'nl-NL'

Code for the language to transcribe.

See supported languages for amazon

Type:

str

PATH_OF_TEMP_CONVERTED_AUDIO_FILE: str = 'converted_audio_file.wav'

path to temp file that will be created to convert the audio files to an accepted audio format.

Type:

PATH_OF_TEMP_CONVERTED_AUDIO_FILE

_append_error(samples, audio_id, error)

Append error to model_errors.

Parameters:

• samples (SampleDataset) – Dataset of audio.

• id (str) – Id of failed sample.

• error (str) – Error message.

_benchmark_sample_with_time(dataset, audio_id, with_cleaning=True)

Benchmark sample for model with timer.

Parameters:

• dataset (Dataset) – Dataset of audio.

• id (str) – Id of audio file.

• with_cleaning (bool, optional) – Set True to clean transcripts. Defaults to True.

Returns:

Metrics of the transcript.

Return type:

Metrics

_get_transcribe_file_location(file_uri, transcribe_client, job_name='Transcribe')

Transcribe and return result location. :raises AmazonNoTranscriptReturned: Exception when API does not return an transcript.

Parameters:

• file_uri (str) – S3 path to audio file.

• () (transcribe_client) – Boto3 transcribe client.

• file_ext (str) – File extention of audio file.

• job_name (str, optional) – Name of amazon AWS job. Defaults to “Transcribe”.

Return type:

str

_get_transcript_from_json_uri(json_uri)

Get transcript from amazon transcribe json result.

Parameters:

json_uri (str) – Uri of the resulting json file.

Returns:

Transcript of the audio.

Return type:

str

benchmark_n_samples(dataset, number_of_samples, with_cleaning=True)

Benchmark n samples with model.

Parameters:

• dataset (Dataset) – Dataset of audio.

• number_of_samples (int) – Number of random samples to benchmerk.

• with_cleaning (bool, optional) – Set True to clean transcripts. Defaults to True.

Returns:

List of metrics for each sample.

Return type:

list

benchmark_sample(dataset, audio_id, with_cleaning=True)

Benchmark sample with model.

Parameters:

• dataset (Dataset) – Dataset of audio.

• id (str) – Id of audio file.

• with_cleaning (bool, optional) – Set True to clean transcripts. Defaults to True.

Returns:

Metrics of the transcript.

Return type:

Metrics

benchmark_samples(samples, with_cleaning=True)

Benchmark samples with model.

Parameters:

• dataset (Dataset) – Dataset of audio.

• number_of_samples (int) – Number of random samples to benchmerk.

• with_cleaning (bool, optional) – Set True to clean transcripts. Defaults to True.

Returns:

List of metrics for each sample.

Return type:

list

convert_sample(path_to_sample)

Convert sample to correct format.

Parameters:

• path_to_sample (str) – Path to sample.

• override (bool, optional) – Override original file. Defaults to False.

Returns:

Path to converted sample.

Return type:

str

get_model()

Get model.