ElevenLabs Tutorial: Build a Word Spelling App with Speech Synthesis

Introduction

In today's fast-paced world of software development, the emergence of generative AI tools is revolutionizing the industry. From generating cover letters and emails to automatic code comment generation, the possibilities are endless. Beyond coding, innovative image generation tools allow users to create visuals from simple text prompts. With the increasing trend of voice commands in user experiences, it only makes sense to incorporate voice features into our software applications. This tutorial will showcase how to utilize the Speech Synthesis feature provided by ElevenLabs within a simple app that generates random words and spells them out. We will leverage Streamlit, an intuitive UI library for building data science projects, to develop our user interface.

Introduction to ElevenLabs

ElevenLabs is a pioneering company specializing in voice technology. They offer a robust speech synthesis solution through an easy-to-use API, enabling developers to generate high-quality speech outputs. The underlying AI model is trained on a vast collection of audiobooks and podcasts, ensuring predictable and high-quality results. ElevenLabs boasts two primary features: VoiceLab, which allows users to clone voices or design them based on various characteristics, and Speech Synthesis, which enables speech generation from either designed or pre-made voices.

Introduction to Anthropic's Claude Model

Claude is the latest AI model developed by Anthropic, an organization focused on enhancing the safety and robustness of AI systems. Designed to generate human-like responses, Claude serves a broad range of applications, including content creation, legal assistance, and customer service. Unlike many AI models trained on diverse internet texts, Claude emphasizes safety, enabling it to refuse harmful or untruthful outputs.

Introduction to Streamlit

Streamlit is an open-source Python library that empowers developers and data scientists to create visually appealing web applications quickly. Its user-friendly API facilitates an easy transition from data scripts to interactive UI components, allowing rapid deployment of fully-featured data science apps.

Prerequisites

• Basic knowledge of Python and UI development using Streamlit
• Access to the Anthropic API
• Access to the ElevenLabs API

Outline

1. Initializing our Streamlit Project
2. Adding Word Generation Feature using Claude Model
3. Adding Speech Generation Feature using ElevenLabs API
4. Testing the Word Generator App

Initializing our Streamlit Project

To kick off our project, begin by creating a directory for the project and navigating into it. This directory will serve as the foundation for our Streamlit application. Since a Streamlit project is essentially a Python project, we will initialize a virtual environment.

Setting Up the Environment

Once your virtual environment is activated, the terminal output will display the name of the virtual environment (e.g., (env)). Next, install the necessary libraries using pip:

pip install streamlit anthropic elevenlabs pydantic

Now that we've satisfied the project's library requirements, let’s create the main application file named randomwords_app.py and open it in your code editor. To start, we'll build a simple UI with a title and a caption.

Running the Initial App

To run the app, ensure that you are in the correct directory with the virtual environment activated. Execute the following command:

streamlit run randomwords_app.py

Your default browser should open, displaying the title and caption of the app. In preparation for the next feature, it’s crucial to include our API keys for the Anthropic and ElevenLabs services. Rather than using a .env file, Streamlit manages environment variables differently through a secret configuration file in a .streamlit directory.

Adding Word Generation Feature using Claude Model

In this section, we'll introduce a button that generates a random word and display the word's meaning. First, import the necessary libraries to utilize the Claude model.

Creating the Word Generation Function

Our word generation function will rely on Anthropic's Claude model. It’s essential to format our queries accurately to maintain consistency across responses. By specifying directives in our prompt, we can ensure that Claude adheres to our desired response structure.

Enhancing the User Interface

We'll update the UI to include containers for our word and its meaning, along with a button to trigger the generation of the word. Streamlit's simplicity allows us to declare click event handlers effortlessly.

Testing the Word Generation Feature

After updating the app, run the same command to see the changes reflected in the UI.

Adding Speech Generation Feature using ElevenLabs API

With our random word generator ready, it’s time to integrate speech generation using ElevenLabs API.

Integrating the Speech Generation Function

By including ElevenLabs' functionality, we can generate speech from the random word. The eleven_multilingual_v1 model is ideal for this task, as it supports multiple languages and accents.

Implementing Audio Playback

We will add an audio player to the interface, enabling users to listen to the generated speech. The audio player will only appear when there’s a word available.

Testing the Complete Application

Run the app again to test the full functionality. Clicking the