AWS SDK を使用して Amazon Transcribe カスタム語彙を作成して絞り込む - Amazon Transcribe

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AWS SDK を使用して Amazon Transcribe カスタム語彙を作成して絞り込む

次のコードサンプルは、以下の操作方法を示しています。

  • Amazon S3 に音声ファイルをアップロードします。

  • Amazon Transcribe ジョブを実行してファイルを文字起こしし、結果を取得します。

  • カスタム語彙を作成して改良し、文字起こしの精度を向上させます。

  • カスタム語彙を使ってジョブを実行し、結果を取得します。

Python
SDK for Python (Boto3)
注記

については、「」を参照してください GitHub。AWS コード例リポジトリ で全く同じ例を見つけて、設定と実行の方法を確認してください。

ルイス キャロルによる「ジャバウォッキー」の朗読を収録した音声ファイルを文字起こしします。まず、Amazon Transcribe アクションをラップする関数を作成します。

def start_job( job_name, media_uri, media_format, language_code, transcribe_client, vocabulary_name=None, ): """ Starts a transcription job. This function returns as soon as the job is started. To get the current status of the job, call get_transcription_job. The job is successfully completed when the job status is 'COMPLETED'. :param job_name: The name of the transcription job. This must be unique for your AWS account. :param media_uri: The URI where the audio file is stored. This is typically in an Amazon S3 bucket. :param media_format: The format of the audio file. For example, mp3 or wav. :param language_code: The language code of the audio file. For example, en-US or ja-JP :param transcribe_client: The Boto3 Transcribe client. :param vocabulary_name: The name of a custom vocabulary to use when transcribing the audio file. :return: Data about the job. """ try: job_args = { "TranscriptionJobName": job_name, "Media": {"MediaFileUri": media_uri}, "MediaFormat": media_format, "LanguageCode": language_code, } if vocabulary_name is not None: job_args["Settings"] = {"VocabularyName": vocabulary_name} response = transcribe_client.start_transcription_job(**job_args) job = response["TranscriptionJob"] logger.info("Started transcription job %s.", job_name) except ClientError: logger.exception("Couldn't start transcription job %s.", job_name) raise else: return job def get_job(job_name, transcribe_client): """ Gets details about a transcription job. :param job_name: The name of the job to retrieve. :param transcribe_client: The Boto3 Transcribe client. :return: The retrieved transcription job. """ try: response = transcribe_client.get_transcription_job( TranscriptionJobName=job_name ) job = response["TranscriptionJob"] logger.info("Got job %s.", job["TranscriptionJobName"]) except ClientError: logger.exception("Couldn't get job %s.", job_name) raise else: return job def delete_job(job_name, transcribe_client): """ Deletes a transcription job. This also deletes the transcript associated with the job. :param job_name: The name of the job to delete. :param transcribe_client: The Boto3 Transcribe client. """ try: transcribe_client.delete_transcription_job(TranscriptionJobName=job_name) logger.info("Deleted job %s.", job_name) except ClientError: logger.exception("Couldn't delete job %s.", job_name) raise def create_vocabulary( vocabulary_name, language_code, transcribe_client, phrases=None, table_uri=None ): """ Creates a custom vocabulary that can be used to improve the accuracy of transcription jobs. This function returns as soon as the vocabulary processing is started. Call get_vocabulary to get the current status of the vocabulary. The vocabulary is ready to use when its status is 'READY'. :param vocabulary_name: The name of the custom vocabulary. :param language_code: The language code of the vocabulary. For example, en-US or nl-NL. :param transcribe_client: The Boto3 Transcribe client. :param phrases: A list of comma-separated phrases to include in the vocabulary. :param table_uri: A table of phrases and pronunciation hints to include in the vocabulary. :return: Information about the newly created vocabulary. """ try: vocab_args = {"VocabularyName": vocabulary_name, "LanguageCode": language_code} if phrases is not None: vocab_args["Phrases"] = phrases elif table_uri is not None: vocab_args["VocabularyFileUri"] = table_uri response = transcribe_client.create_vocabulary(**vocab_args) logger.info("Created custom vocabulary %s.", response["VocabularyName"]) except ClientError: logger.exception("Couldn't create custom vocabulary %s.", vocabulary_name) raise else: return response def get_vocabulary(vocabulary_name, transcribe_client): """ Gets information about a custom vocabulary. :param vocabulary_name: The name of the vocabulary to retrieve. :param transcribe_client: The Boto3 Transcribe client. :return: Information about the vocabulary. """ try: response = transcribe_client.get_vocabulary(VocabularyName=vocabulary_name) logger.info("Got vocabulary %s.", response["VocabularyName"]) except ClientError: logger.exception("Couldn't get vocabulary %s.", vocabulary_name) raise else: return response def update_vocabulary( vocabulary_name, language_code, transcribe_client, phrases=None, table_uri=None ): """ Updates an existing custom vocabulary. The entire vocabulary is replaced with the contents of the update. :param vocabulary_name: The name of the vocabulary to update. :param language_code: The language code of the vocabulary. :param transcribe_client: The Boto3 Transcribe client. :param phrases: A list of comma-separated phrases to include in the vocabulary. :param table_uri: A table of phrases and pronunciation hints to include in the vocabulary. """ try: vocab_args = {"VocabularyName": vocabulary_name, "LanguageCode": language_code} if phrases is not None: vocab_args["Phrases"] = phrases elif table_uri is not None: vocab_args["VocabularyFileUri"] = table_uri response = transcribe_client.update_vocabulary(**vocab_args) logger.info("Updated custom vocabulary %s.", response["VocabularyName"]) except ClientError: logger.exception("Couldn't update custom vocabulary %s.", vocabulary_name) raise def list_vocabularies(vocabulary_filter, transcribe_client): """ Lists the custom vocabularies created for this AWS account. :param vocabulary_filter: The returned vocabularies must contain this string in their names. :param transcribe_client: The Boto3 Transcribe client. :return: The list of retrieved vocabularies. """ try: response = transcribe_client.list_vocabularies(NameContains=vocabulary_filter) vocabs = response["Vocabularies"] next_token = response.get("NextToken") while next_token is not None: response = transcribe_client.list_vocabularies( NameContains=vocabulary_filter, NextToken=next_token ) vocabs += response["Vocabularies"] next_token = response.get("NextToken") logger.info( "Got %s vocabularies with filter %s.", len(vocabs), vocabulary_filter ) except ClientError: logger.exception( "Couldn't list vocabularies with filter %s.", vocabulary_filter ) raise else: return vocabs def delete_vocabulary(vocabulary_name, transcribe_client): """ Deletes a custom vocabulary. :param vocabulary_name: The name of the vocabulary to delete. :param transcribe_client: The Boto3 Transcribe client. """ try: transcribe_client.delete_vocabulary(VocabularyName=vocabulary_name) logger.info("Deleted vocabulary %s.", vocabulary_name) except ClientError: logger.exception("Couldn't delete vocabulary %s.", vocabulary_name) raise

ラッパー関数を呼び出して、カスタム語彙なしで音声を文字起こししてから、カスタム語彙の異なるバージョンで文字起こしを行うと、よりよい結果が取得できます。

def usage_demo(): """Shows how to use the Amazon Transcribe service.""" logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") s3_resource = boto3.resource("s3") transcribe_client = boto3.client("transcribe") print("-" * 88) print("Welcome to the Amazon Transcribe demo!") print("-" * 88) bucket_name = f"jabber-bucket-{time.time_ns()}" print(f"Creating bucket {bucket_name}.") bucket = s3_resource.create_bucket( Bucket=bucket_name, CreateBucketConfiguration={ "LocationConstraint": transcribe_client.meta.region_name }, ) media_file_name = ".media/Jabberwocky.mp3" media_object_key = "Jabberwocky.mp3" print(f"Uploading media file {media_file_name}.") bucket.upload_file(media_file_name, media_object_key) media_uri = f"s3://{bucket.name}/{media_object_key}" job_name_simple = f"Jabber-{time.time_ns()}" print(f"Starting transcription job {job_name_simple}.") start_job( job_name_simple, f"s3://{bucket_name}/{media_object_key}", "mp3", "en-US", transcribe_client, ) transcribe_waiter = TranscribeCompleteWaiter(transcribe_client) transcribe_waiter.wait(job_name_simple) job_simple = get_job(job_name_simple, transcribe_client) transcript_simple = requests.get( job_simple["Transcript"]["TranscriptFileUri"] ).json() print(f"Transcript for job {transcript_simple['jobName']}:") print(transcript_simple["results"]["transcripts"][0]["transcript"]) print("-" * 88) print( "Creating a custom vocabulary that lists the nonsense words to try to " "improve the transcription." ) vocabulary_name = f"Jabber-vocabulary-{time.time_ns()}" create_vocabulary( vocabulary_name, "en-US", transcribe_client, phrases=[ "brillig", "slithy", "borogoves", "mome", "raths", "Jub-Jub", "frumious", "manxome", "Tumtum", "uffish", "whiffling", "tulgey", "thou", "frabjous", "callooh", "callay", "chortled", ], ) vocabulary_ready_waiter = VocabularyReadyWaiter(transcribe_client) vocabulary_ready_waiter.wait(vocabulary_name) job_name_vocabulary_list = f"Jabber-vocabulary-list-{time.time_ns()}" print(f"Starting transcription job {job_name_vocabulary_list}.") start_job( job_name_vocabulary_list, media_uri, "mp3", "en-US", transcribe_client, vocabulary_name, ) transcribe_waiter.wait(job_name_vocabulary_list) job_vocabulary_list = get_job(job_name_vocabulary_list, transcribe_client) transcript_vocabulary_list = requests.get( job_vocabulary_list["Transcript"]["TranscriptFileUri"] ).json() print(f"Transcript for job {transcript_vocabulary_list['jobName']}:") print(transcript_vocabulary_list["results"]["transcripts"][0]["transcript"]) print("-" * 88) print( "Updating the custom vocabulary with table data that provides additional " "pronunciation hints." ) table_vocab_file = "jabber-vocabulary-table.txt" bucket.upload_file(table_vocab_file, table_vocab_file) update_vocabulary( vocabulary_name, "en-US", transcribe_client, table_uri=f"s3://{bucket.name}/{table_vocab_file}", ) vocabulary_ready_waiter.wait(vocabulary_name) job_name_vocab_table = f"Jabber-vocab-table-{time.time_ns()}" print(f"Starting transcription job {job_name_vocab_table}.") start_job( job_name_vocab_table, media_uri, "mp3", "en-US", transcribe_client, vocabulary_name=vocabulary_name, ) transcribe_waiter.wait(job_name_vocab_table) job_vocab_table = get_job(job_name_vocab_table, transcribe_client) transcript_vocab_table = requests.get( job_vocab_table["Transcript"]["TranscriptFileUri"] ).json() print(f"Transcript for job {transcript_vocab_table['jobName']}:") print(transcript_vocab_table["results"]["transcripts"][0]["transcript"]) print("-" * 88) print("Getting data for jobs and vocabularies.") jabber_jobs = list_jobs("Jabber", transcribe_client) print(f"Found {len(jabber_jobs)} jobs:") for job_sum in jabber_jobs: job = get_job(job_sum["TranscriptionJobName"], transcribe_client) print( f"\t{job['TranscriptionJobName']}, {job['Media']['MediaFileUri']}, " f"{job['Settings'].get('VocabularyName')}" ) jabber_vocabs = list_vocabularies("Jabber", transcribe_client) print(f"Found {len(jabber_vocabs)} vocabularies:") for vocab_sum in jabber_vocabs: vocab = get_vocabulary(vocab_sum["VocabularyName"], transcribe_client) vocab_content = requests.get(vocab["DownloadUri"]).text print(f"\t{vocab['VocabularyName']} contents:") print(vocab_content) print("-" * 88) print("Deleting demo jobs.") for job_name in [job_name_simple, job_name_vocabulary_list, job_name_vocab_table]: delete_job(job_name, transcribe_client) print("Deleting demo vocabulary.") delete_vocabulary(vocabulary_name, transcribe_client) print("Deleting demo bucket.") bucket.objects.delete() bucket.delete() print("Thanks for watching!")

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