Pengenal

Speech-to-Text V2 mendukung resource Google Cloud yang disebut pengenal. Pengenal merepresentasikan konfigurasi pengenalan yang tersimpan dan dapat digunakan kembali. Anda dapat menggunakannya untuk mengelompokkan transkripsi atau traffic secara logis untuk aplikasi Anda.

Sebelum memulai

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Google Cloud project.

  4. Enable the Speech-to-Text APIs.

    Enable the APIs

  5. Make sure that you have the following role or roles on the project: Cloud Speech Administrator

    Check for the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

    4. For all rows that specify or include you, check the Role column to see whether the list of roles includes the required roles.

    Grant the roles

    1. In the Google Cloud console, go to the IAM page.

      Buka IAM
    2. Pilih project.
    3. Klik Berikan akses.
    4. Di kolom Akun utama baru, masukkan ID pengguna Anda. Biasanya berupa alamat email untuk Akun Google.

    5. Di daftar Pilih peran, pilih peran.
    6. Untuk memberikan peran tambahan, klik Tambahkan peran lain, lalu tambahkan setiap peran tambahan.
    7. Klik Simpan.
  6. Install the Google Cloud CLI.

  7. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  8. To initialize the gcloud CLI, run the following command:

    gcloud init
  9. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  10. Make sure that billing is enabled for your Google Cloud project.

  11. Enable the Speech-to-Text APIs.

    Enable the APIs

  12. Make sure that you have the following role or roles on the project: Cloud Speech Administrator

    Check for the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

    4. For all rows that specify or include you, check the Role column to see whether the list of roles includes the required roles.

    Grant the roles

    1. In the Google Cloud console, go to the IAM page.

      Buka IAM
    2. Pilih project.
    3. Klik Berikan akses.
    4. Di kolom Akun utama baru, masukkan ID pengguna Anda. Biasanya berupa alamat email untuk Akun Google.

    5. Di daftar Pilih peran, pilih peran.
    6. Untuk memberikan peran tambahan, klik Tambahkan peran lain, lalu tambahkan setiap peran tambahan.
    7. Klik Simpan.
  13. Install the Google Cloud CLI.

  14. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  15. To initialize the gcloud CLI, run the following command:

    gcloud init
  16. Library klien dapat menggunakan Kredensial Default Aplikasi untuk dengan mudah melakukan autentikasi dengan Google API dan mengirim permintaan ke API tersebut. Dengan Kredensial Default Aplikasi, Anda dapat menguji aplikasi secara lokal dan men-deploy aplikasi tanpa mengubah kode yang mendasarinya. Untuk mengetahui informasi selengkapnya, lihat Melakukan autentikasi untuk menggunakan library klien.

  17. If you're using a local shell, then create local authentication credentials for your user account:

    gcloud auth application-default login

    You don't need to do this if you're using Cloud Shell.

    If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

  18. Selain itu, pastikan Anda telah menginstal library klien.

    Memahami pengenal

    Pengenal adalah konfigurasi pengenalan yang dapat dikonfigurasi dan dapat digunakan kembali. Membuat pengenal dengan konfigurasi pengenalan yang sering digunakan akan membantu menyederhanakan dan mengurangi ukuran permintaan pengenalan.

    Elemen inti pengenal adalah konfigurasi default-nya. Ini adalah konfigurasi untuk setiap permintaan pengenalan yang dilakukan pengenal ini. Anda dapat mengganti nilai default ini per permintaan. Pertahankan konfigurasi default untuk fitur yang Anda perlukan di seluruh permintaan untuk pengenal tertentu, sekaligus ganti fitur spesifik untuk permintaan tertentu.

    Gunakan kembali pengenal sesering mungkin. Membuat satu pengenal untuk setiap permintaan akan meningkatkan latensi aplikasi secara drastis dan menghabiskan kuota resource Anda. Buat pengenal sesekali saja selama integrasi dan penyiapan, lalu gunakan kembali untuk permintaan pengenalan.

    Membuat pengenal

    Berikut adalah contoh cara membuat pengenal yang dapat digunakan untuk mengirim permintaan pengenalan:

    Python

    import os
    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    
    PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
    
    
    def create_recognizer(recognizer_id: str) -> cloud_speech.Recognizer:
        """Сreates a recognizer with an unique ID and default recognition configuration.
        Args:
            recognizer_id (str): The unique identifier for the recognizer to be created.
        Returns:
            cloud_speech.Recognizer: The created recognizer object with configuration.
        """
        # Instantiates a client
        client = SpeechClient()
    
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    language_codes=["en-US"], model="long"
                ),
            ),
        )
        # Sends the request to create a recognizer and waits for the operation to complete
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
    
        print("Created Recognizer:", recognizer.name)
        return recognizer
    
    

    Menggunakan pengenal yang ada untuk mengirim permintaan

    Berikut adalah contoh cara mengirim beberapa permintaan pengenalan menggunakan pengenal yang sama:

    Python

    import os
    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    
    PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
    
    
    def transcribe_reuse_recognizer(
        audio_file: str,
        recognizer_id: str,
    ) -> cloud_speech.RecognizeResponse:
        """Transcribe an audio file using an existing recognizer.
        Args:
            audio_file (str): Path to the local audio file to be transcribed.
                Example: "resources/audio.wav"
            recognizer_id (str): The ID of the existing recognizer to be used for transcription.
        Returns:
            cloud_speech.RecognizeResponse: The response containing the transcription results.
        """
        # Instantiates a client
        client = SpeechClient()
    
        # Reads a file as bytes
        with open(audio_file, "rb") as f:
            audio_content = f.read()
    
        request = cloud_speech.RecognizeRequest(
            recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
            content=audio_content,
        )
    
        # Transcribes the audio into text
        response = client.recognize(request=request)
    
        for result in response.results:
            print(f"Transcript: {result.alternatives[0].transcript}")
    
        return response
    
    

    Mengaktifkan fitur di pengenal

    Pengenal dapat digunakan untuk mengaktifkan berbagai fitur dalam pengenalan, seperti tanda baca otomatis atau pemfilteran kata-kata tidak sopan.

    Berikut adalah contoh cara mengaktifkan tanda baca otomatis dalam sebuah pengenal yang mengaktifkan tanda baca otomatis dalam permintaan pengenalan menggunakan pengenal ini:

    Python

    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    
    from google.api_core.exceptions import NotFound
    
    # Instantiates a client
    client = SpeechClient()
    
    # TODO(developer): Update and un-comment below line
    # PROJECT_ID = "your-project-id"
    # recognizer_id = "id-recognizer"
    recognizer_name = (
        f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}"
    )
    try:
        # Use an existing recognizer
        recognizer = client.get_recognizer(name=recognizer_name)
        print("Using existing Recognizer:", recognizer.name)
    except NotFound:
        # Create a new recognizer
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
                    language_codes=["en-US"],
                    model="latest_long",
                    features=cloud_speech.RecognitionFeatures(
                        enable_automatic_punctuation=True,
                    ),
                ),
            ),
        )
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
        print("Created Recognizer:", recognizer.name)
    
    # Reads a file as bytes
    with open(audio_file, "rb") as f:
        audio_content = f.read()
    
    request = cloud_speech.RecognizeRequest(
        recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
        content=audio_content,
    )
    
    # Transcribes the audio into text
    response = client.recognize(request=request)
    
    for result in response.results:
        print(f"Transcript: {result.alternatives[0].transcript}")
    

    Mengganti fitur pengenal dalam permintaan pengenalan

    Berikut adalah contoh cara mengaktifkan beberapa fitur dalam sebuah pengenal, tetapi menonaktifkan tanda baca otomatis untuk permintaan pengenalan ini:

    Python

    import os
    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    from google.protobuf.field_mask_pb2 import FieldMask
    
    PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
    
    
    def transcribe_override_recognizer(
        audio_file: str,
        recognizer_id: str,
    ) -> cloud_speech.RecognizeResponse:
        """Transcribe an audio file using an existing recognizer with overridden settings for the recognition request.
        Args:
            audio_file (str): Path to the local audio file to be transcribed.
                Example: "resources/audio.wav"
            recognizer_id (str): The unique ID of the recognizer to be used for transcription.
        Returns:
            cloud_speech.RecognizeResponse: The response containing the transcription results.
        """
        # Instantiates a client
        client = SpeechClient()
    
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
                    language_codes=["en-US"],
                    model="latest_long",
                    features=cloud_speech.RecognitionFeatures(
                        enable_automatic_punctuation=True,
                        enable_word_time_offsets=True,
                    ),
                ),
            ),
        )
    
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
    
        print("Created Recognizer:", recognizer.name)
    
        # Reads a file as bytes
        with open(audio_file, "rb") as f:
            audio_content = f.read()
    
        request = cloud_speech.RecognizeRequest(
            recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
            config=cloud_speech.RecognitionConfig(
                features=cloud_speech.RecognitionFeatures(
                    enable_word_time_offsets=False,
                ),
            ),
            config_mask=FieldMask(paths=["features.enable_word_time_offsets"]),
            content=audio_content,
        )
    
        # Transcribes the audio into text
        response = client.recognize(request=request)
    
        for result in response.results:
            print(f"Transcript: {result.alternatives[0].transcript}")
    
        return response
    
    

    Mengirim permintaan tanpa pengenal

    Pengenal dalam permintaan pengenalan bersifat opsional. Untuk membuat permintaan tanpa pengenal, cukup gunakan ID resource pengenal _ di lokasi Anda membuat permintaan. Berikut ini contohnya:

    Python

    import os
    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    
    PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
    
    
    def quickstart_v2(audio_file: str) -> cloud_speech.RecognizeResponse:
        """Transcribe an audio file.
        Args:
            audio_file (str): Path to the local audio file to be transcribed.
        Returns:
            cloud_speech.RecognizeResponse: The response from the recognize request, containing
            the transcription results
        """
        # Reads a file as bytes
        with open(audio_file, "rb") as f:
            audio_content = f.read()
    
        # Instantiates a client
        client = SpeechClient()
    
        config = cloud_speech.RecognitionConfig(
            auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
            language_codes=["en-US"],
            model="long",
        )
    
        request = cloud_speech.RecognizeRequest(
            recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/_",
            config=config,
            content=audio_content,
        )
    
        # Transcribes the audio into text
        response = client.recognize(request=request)
    
        for result in response.results:
            print(f"Transcript: {result.alternatives[0].transcript}")
    
        return response
    
    

    Pembersihan

    Agar akun Google Cloud Anda tidak dikenai biaya untuk resource yang digunakan di halaman ini, ikuti langkah-langkah berikut.

    1. Optional: Revoke the authentication credentials that you created, and delete the local credential file.

      gcloud auth application-default revoke
    2. Optional: Revoke credentials from the gcloud CLI.

      gcloud auth revoke

    Konsol

  19. In the Google Cloud console, go to the Manage resources page.

    Go to Manage resources

  20. In the project list, select the project that you want to delete, and then click Delete.
  21. In the dialog, type the project ID, and then click Shut down to delete the project.
  22. gcloud

    Delete a Google Cloud project:

    gcloud projects delete PROJECT_ID

    Langkah berikutnya