Google Cloud Text-to-Speech API 'Speaking Addresses with SSML' Tutorial Python Samples

.. image:: https://gstatic.com/cloudssh/images/open-btn.png

:target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=/README.rst

This directory contains samples for Google Cloud Text-to-Speech API 'Speaking Addresses with SSML' Tutorial. Google Cloud Text-To-Speech API 'Speaking Addresses with SSML Tutorial'_ enables you to use Speech Synthesis Markup Language (SSML) to speak a text file of addresses. You can embed SSML commands in a string of text to personalize synthetic audio from Cloud Text-to-Speech API.

.. _Google Cloud Text-to-Speech API 'Speaking Addresses with SSML' Tutorial: https://cloud.google.com/text-to-speech/docs/ssml-tutorial

Setup

Authentication

This sample requires you to have authentication setup. Refer to the

`Authentication Getting Started Guide`_ for instructions on setting up

credentials for applications.

.. _Authentication Getting Started Guide:

https://cloud.google.com/docs/authentication/getting-started

Install Dependencies

#. Clone python-docs-samples and change directory to the sample directory you want to use.

.. code-block:: bash

#. Install `pip`_ and `virtualenv`_ if you do not already have them. You may want to refer to the `Python Development Environment Setup Guide`_ for Google Cloud Platform for instructions.

.. _Python Development Environment Setup Guide:

https://cloud.google.com/python/setup

#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

.. code-block:: bash

#. Install the dependencies needed to run the samples.

.. code-block:: bash

.. _pip: https://pip.pypa.io/

.. _virtualenv: https://virtualenv.pypa.io/

Samples

Speaking addresses with SSML Tutorial

.. image:: https://gstatic.com/cloudssh/images/open-btn.png

:target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=/tts.py,/README.rst

To run this sample:

.. code-block:: bash

The client library

This sample uses the `Google Cloud Client Library for Python`_.

You can read the documentation for more details on API usage and use GitHub

to `browse the source`_ and `report issues`_.

.. _Google Cloud Client Library for Python:

https://googlecloudplatform.github.io/google-cloud-python/

.. _browse the source:

https://github.com/GoogleCloudPlatform/google-cloud-python

.. _report issues:

https://github.com/GoogleCloudPlatform/google-cloud-python/issues

.. _Google Cloud SDK: https://cloud.google.com/sdk/

# This file is used to generate README.rst

product:

name: Google Cloud Text-to-Speech API 'Speaking Addresses with SSML' Tutorial

short_name: Cloud TTS API SSML Addresses Tutorial

url: https://cloud.google.com/text-to-speech/docs/ssml-tutorial

description: >

Google Cloud Text-To-Speech API 'Speaking Addresses with SSML Tutorial'_ enables you to use Speech Synthesis Markup Language (SSML) to speak a text file of addresses. You can embed SSML commands in a string of text to personalize synthetic audio from Cloud Text-to-Speech API.

setup:

- auth

- install_deps

samples:

- name: Speaking addresses with SSML Tutorial

file: tts.py

cloud_client_library: true

<speak>123 Street Ln, Small Town, IL 12345 USA

<break time="2s"/>1 Jenny St &amp; Number St, Tutone City, CA 86753

<break time="2s"/>1 Piazza del Fibonacci, 12358 Pisa, Italy

<break time="2s"/></speak>

123 Street Ln, Small Town, IL 12345 USA

1 Jenny St & Number St, Tutone City, CA 86753

1 Piazza del Fibonacci, 12358 Pisa, Italy

from google.cloud import texttospeech

import cgi

def ssml_to_audio(ssml_text, outfile):

# Generates SSML text from plaintext.

#

# Given a string of SSML text and an output file name, this function

# calls the Text-to-Speech API. The API returns a synthetic audio

# version of the text, formatted according to the SSML commands. This

# function saves the synthetic audio to the designated output file.

#

# Args:

# ssml_text: string of SSML text

# outfile: string name of file under which to save audio output

#

# Returns:

# nothing

# Instantiates a client

client = texttospeech.TextToSpeechClient()

# Sets the text input to be synthesized

synthesis_input = texttospeech.types.SynthesisInput(ssml=ssml_text)

# Builds the voice request, selects the language code ("en-US") and

# the SSML voice gender ("MALE")

voice = texttospeech.types.VoiceSelectionParams(

language_code='en-US',

ssml_gender=texttospeech.enums.SsmlVoiceGender.MALE)

# Selects the type of audio file to return

audio_config = texttospeech.types.AudioConfig(

audio_encoding=texttospeech.enums.AudioEncoding.MP3)

# Performs the text-to-speech request on the text input with the selected

# voice parameters and audio file type

response = client.synthesize_speech(synthesis_input, voice, audio_config)

# Writes the synthetic audio to the output file.

with open(outfile, 'wb') as out:

out.write(response.audio_content)

print('Audio content written to file ' + outfile)

# [END tts_ssml_address_audio]

def text_to_ssml(inputfile):

# Generates SSML text from plaintext.

# Given an input filename, this function converts the contents of the text

# file into a string of formatted SSML text. This function formats the SSML

# string so that, when synthesized, the synthetic audio will pause for two

# seconds between each line of the text file. This function also handles

# special text characters which might interfere with SSML commands.

#

# Args:

# inputfile: string name of plaintext file

#

# Returns:

# A string of SSML text based on plaintext input

# Parses lines of input file

with open(inputfile, 'r') as f:

raw_lines = f.read()

# Replace special characters with HTML Ampersand Character Codes

# These Codes prevent the API from confusing text with

# SSML commands

# For example, '<' --> '&lt;' and '&' --> '&amp;'

# For Python 3, instead use:

# escaped_lines = html.escape(raw_lines)

escaped_lines = cgi.escape(raw_lines)

# Convert plaintext to SSML

# Wait two seconds between each address

ssml = '<speak>{}</speak>'.format(

escaped_lines.replace('\n', '\n<break time="2s"/>'))

# Return the concatenated string of ssml script

return ssml

def main():

# test example address file

plaintext = 'resources/example.txt'

ssml_text = text_to_ssml(plaintext)

ssml_to_audio(ssml_text, 'resources/example.mp3')

# [END tts_ssml_address_test]

if __name__ == '__main__':

main()

from tts import text_to_ssml

from tts import ssml_to_audio

import filecmp

import os

def test_text_to_ssml(capsys):

# Read expected SSML output from resources

with open('resources/example.ssml', 'r') as f:

expected_ssml = f.read()

# Assert plaintext converted to SSML

input_text = 'resources/example.txt'

tested_ssml = text_to_ssml(input_text)

assert expected_ssml == tested_ssml

def test_ssml_to_audio(capsys):

# Read SSML input from resources

with open('resources/example.ssml', 'r') as f:

input_ssml = f.read()

# Assert audio file generated

ssml_to_audio(input_ssml, 'test_example.mp3')

assert os.path.isfile('test_example.mp3')

# Assert audio file generated correctly

assert filecmp.cmp('test_example.mp3',

'resources/expected_example.mp3',

shallow=True)

out, err = capsys.readouterr()

# Delete test file

os.remove("test_example.mp3")

# Assert success message printed

assert "Audio content written to file test_example.mp3" in out