StartTranscriptionJob 搭配 a AWS SDK 或 CLI 使用 - AWS SDK 程式碼範例

文件 AWS SDK AWS 範例 SDK 儲存庫中有更多可用的 GitHub 範例。

本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。

StartTranscriptionJob 搭配 a AWS SDK 或 CLI 使用

下列程式碼範例示範如何使用 StartTranscriptionJob

動作範例是大型程式的程式碼摘錄,必須在內容中執行。您可以在下列程式碼範例的內容中看到此動作:

.NET
AWS SDK for .NET
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

/// <summary> /// Start a transcription job for a media file. This method returns /// as soon as the job is started. /// </summary> /// <param name="jobName">A unique name for the transcription job.</param> /// <param name="mediaFileUri">The URI of the media file, typically an Amazon S3 location.</param> /// <param name="mediaFormat">The format of the media file.</param> /// <param name="languageCode">The language code of the media file, such as en-US.</param> /// <param name="vocabularyName">Optional name of a custom vocabulary.</param> /// <returns>A TranscriptionJob instance with information on the new job.</returns> public async Task<TranscriptionJob> StartTranscriptionJob(string jobName, string mediaFileUri, MediaFormat mediaFormat, LanguageCode languageCode, string? vocabularyName) { var response = await _amazonTranscribeService.StartTranscriptionJobAsync( new StartTranscriptionJobRequest() { TranscriptionJobName = jobName, Media = new Media() { MediaFileUri = mediaFileUri }, MediaFormat = mediaFormat, LanguageCode = languageCode, Settings = vocabularyName != null ? new Settings() { VocabularyName = vocabularyName } : null }); return response.TranscriptionJob; }
CLI
AWS CLI

範例 1:轉錄音訊檔案

以下 start-transcription-job 範例會轉錄您的音訊檔案。

aws transcribe start-transcription-job \ --cli-input-json file://myfile.json

myfile.json 的內容:

{ "TranscriptionJobName": "cli-simple-transcription-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" } }

如需詳細資訊,請參閱 Amazon Transcribe 開發人員指南中的入門 (AWS 命令列介面)

範例 2:轉錄多聲道音訊檔案

以下 start-transcription-job 範例會轉錄您的多聲道音訊檔案。

aws transcribe start-transcription-job \ --cli-input-json file://mysecondfile.json

mysecondfile.json 的內容:

{ "TranscriptionJobName": "cli-channelid-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "Settings":{ "ChannelIdentification":true } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-channelid-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "StartTime": "2020-09-17T16:07:56.817000+00:00", "CreationTime": "2020-09-17T16:07:56.784000+00:00", "Settings": { "ChannelIdentification": true } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的轉錄多聲道音訊

範例 3:轉錄音訊檔案並識別不同的發言者

以下 start-transcription-job 範例會轉錄音訊檔案,並識別轉錄輸出中的發言者。

aws transcribe start-transcription-job \ --cli-input-json file://mythirdfile.json

mythirdfile.json 的內容:

{ "TranscriptionJobName": "cli-speakerid-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "Settings":{ "ShowSpeakerLabels": true, "MaxSpeakerLabels": 2 } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-speakerid-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "StartTime": "2020-09-17T16:22:59.696000+00:00", "CreationTime": "2020-09-17T16:22:59.676000+00:00", "Settings": { "ShowSpeakerLabels": true, "MaxSpeakerLabels": 2 } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的識別發言者

範例 4:轉錄音訊檔案,並在轉錄輸出中為任何不希望出現的字詞加上遮罩

以下 start-transcription-job 範例會轉錄音訊檔案,並使用您先前建立的詞彙篩選器來為任何不希望出現的字詞加上遮罩。

aws transcribe start-transcription-job \ --cli-input-json file://myfourthfile.json

myfourthfile.json 的內容:

{ "TranscriptionJobName": "cli-filter-mask-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "Settings":{ "VocabularyFilterName": "your-vocabulary-filter", "VocabularyFilterMethod": "mask" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-filter-mask-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension" }, "StartTime": "2020-09-18T16:36:18.568000+00:00", "CreationTime": "2020-09-18T16:36:18.547000+00:00", "Settings": { "VocabularyFilterName": "your-vocabulary-filter", "VocabularyFilterMethod": "mask" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的篩選轉錄

範例 5:轉錄音訊檔案,並移除轉錄輸出中任何不希望出現的字詞

以下 start-transcription-job 範例會轉錄音訊檔案,並使用您先前建立的詞彙篩選器來為任何不希望出現的字詞加上遮罩。

aws transcribe start-transcription-job \ --cli-input-json file://myfifthfile.json

myfifthfile.json 的內容:

{ "TranscriptionJobName": "cli-filter-remove-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "Settings":{ "VocabularyFilterName": "your-vocabulary-filter", "VocabularyFilterMethod": "remove" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-filter-remove-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "StartTime": "2020-09-18T16:36:18.568000+00:00", "CreationTime": "2020-09-18T16:36:18.547000+00:00", "Settings": { "VocabularyFilterName": "your-vocabulary-filter", "VocabularyFilterMethod": "remove" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的篩選轉錄

範例 6:使用自訂詞彙以更準確的方式轉錄音訊檔案

以下 start-transcription-job 範例會轉錄音訊檔案,並使用您先前建立的詞彙篩選器來為任何不希望出現的字詞加上遮罩。

aws transcribe start-transcription-job \ --cli-input-json file://mysixthfile.json

mysixthfile.json 的內容:

{ "TranscriptionJobName": "cli-vocab-job", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "Settings":{ "VocabularyName": "your-vocabulary" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-vocab-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "the-language-of-your-transcription-job", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "StartTime": "2020-09-18T16:36:18.568000+00:00", "CreationTime": "2020-09-18T16:36:18.547000+00:00", "Settings": { "VocabularyName": "your-vocabulary" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的篩選轉錄

範例 7:識別音訊檔案的語言並進行轉錄

以下 start-transcription-job 範例會轉錄音訊檔案,並使用您先前建立的詞彙篩選器來為任何不希望出現的字詞加上遮罩。

aws transcribe start-transcription-job \ --cli-input-json file://myseventhfile.json

myseventhfile.json 的內容:

{ "TranscriptionJobName": "cli-identify-language-transcription-job", "IdentifyLanguage": true, "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-identify-language-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension" }, "StartTime": "2020-09-18T22:27:23.970000+00:00", "CreationTime": "2020-09-18T22:27:23.948000+00:00", "IdentifyLanguage": true } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的識別語言

範例 8:轉錄包含已修訂的個人身分識別資訊的音訊檔案

以下 start-transcription-job 範例會轉錄音訊檔案,並修訂轉錄輸出中的任何個人身分識別資訊。

aws transcribe start-transcription-job \ --cli-input-json file://myeighthfile.json

myeigthfile.json 的內容:

{ "TranscriptionJobName": "cli-redaction-job", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension" }, "ContentRedaction": { "RedactionOutput":"redacted", "RedactionType":"PII" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-redaction-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension" }, "StartTime": "2020-09-25T23:49:13.195000+00:00", "CreationTime": "2020-09-25T23:49:13.176000+00:00", "ContentRedaction": { "RedactionType": "PII", "RedactionOutput": "redacted" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的自動內容修訂

範例 9:產生已編輯個人識別資訊 (PII) 的文字記錄和未編輯的文字記錄

以下 start-transcription-job 範例會產生音訊檔案的兩個轉錄,一個包含已修訂的個人身分識別資訊,另一個則不包含任何修訂。

aws transcribe start-transcription-job \ --cli-input-json file://myninthfile.json

myninthfile.json 的內容:

{ "TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension" }, "ContentRedaction": { "RedactionOutput":"redacted_and_unredacted", "RedactionType":"PII" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension" }, "StartTime": "2020-09-25T23:59:47.677000+00:00", "CreationTime": "2020-09-25T23:59:47.653000+00:00", "ContentRedaction": { "RedactionType": "PII", "RedactionOutput": "redacted_and_unredacted" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的自動內容修訂

範例 10:使用您先前建立的自訂語言模型來轉錄音訊檔案。

以下 start-transcription-job 範例會使用您先前建立的自訂語言模型來轉錄音訊檔案。

aws transcribe start-transcription-job \ --cli-input-json file://mytenthfile.json

mytenthfile.json 的內容:

{ "TranscriptionJobName": "cli-clm-2-job-1", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension" }, "ModelSettings": { "LanguageModelName":"cli-clm-2" } }

輸出:

{ "TranscriptionJob": { "TranscriptionJobName": "cli-clm-2-job-1", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension" }, "StartTime": "2020-09-28T17:56:01.835000+00:00", "CreationTime": "2020-09-28T17:56:01.801000+00:00", "ModelSettings": { "LanguageModelName": "cli-clm-2" } } }

如需詳細資訊,請參閱《Amazon Transcribe 開發人員指南》中的使用自訂語言模型改善特定領域的轉錄準確性

JavaScript
SDK for JavaScript (v3)
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

開始轉錄作業。

// Import the required AWS SDK clients and commands for Node.js import { StartTranscriptionJobCommand } from "@aws-sdk/client-transcribe"; import { transcribeClient } from "./libs/transcribeClient.js"; // Set the parameters export const params = { TranscriptionJobName: "JOB_NAME", LanguageCode: "LANGUAGE_CODE", // For example, 'en-US' MediaFormat: "SOURCE_FILE_FORMAT", // For example, 'wav' Media: { MediaFileUri: "SOURCE_LOCATION", // For example, "https://transcribe-demo.s3-REGION.amazonaws.com/hello_world.wav" }, OutputBucketName: "OUTPUT_BUCKET_NAME", }; export const run = async () => { try { const data = await transcribeClient.send( new StartTranscriptionJobCommand(params), ); console.log("Success - put", data); return data; // For unit tests. } catch (err) { console.log("Error", err); } }; run();

建立用戶端。

import { TranscribeClient } from "@aws-sdk/client-transcribe"; // Set the AWS Region. const REGION = "REGION"; //e.g. "us-east-1" // Create an Amazon Transcribe service client object. const transcribeClient = new TranscribeClient({ region: REGION }); export { transcribeClient };
Python
SDK for Python (Boto3)
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

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
  • 如需 API 詳細資訊,請參閱 StartTranscriptionJob AWS SDK for Python (Boto3) Word 參考中的 API