Ever wonder how speech generation works? Look no further than our ultimate guide to speech generation. Discover everything you need to know.

Speech generation: The ultimate guide

Speech generation is a rapidly advancing field of artificial intelligence that enables computers to generate human-like speech. In recent years, this AI technology has seen a dramatic improvement in both the quality and naturalness of synthesized speech, thanks to advancements in deep learning and neural networks. In this ultimate guide, we will explore the basics of speech generation, and the different approaches and techniques used to generate human-like speech,

Introduction to speech generation

Speech generation, also known as speech synthesis, is the process of creating artificial human speech that can be heard through a device or computer. This technology has come a long way, with modern systems producing high-quality, natural-sounding speech in real time.

Text to speech synthesis

Speech generation is also known as text to speech (TTS), which means that it converts written or text input into spoken or audible output. TTS technology uses various algorithms and techniques to generate human-like speech from written text.

Speech generation methods

There are three main types of speech generation text to speech techniques used in the industry:

1. Concatenative TTS — Concatenative TTS uses a database of pre-recorded human speech samples, which are concatenated or pieced together to create new synthesized speech. This approach produces high-quality, natural-sounding speech but requires a large amount of data and can be computationally intensive. This approach is often used to create custom voices or voice cloning.
2. Statistical Parametric TTS — The Statistical Parametric TTS system generates speech using mathematical models that simulate the vocal tract and acoustic properties of human speech. This approach requires less data and computational power than concatenative TTS and can be easily adapted to different languages and voices.
3. Hybrid approach — A hybrid approach combines both techniques to generate speech and is also known as Unit Selection Synthesis. This approach uses pre-recorded speech samples as well as mathematical models to produce natural-sounding speech. Each technique has its own advantages and limitations, and the choice of technique depends on the specific application and resources available.

Neural text to speech synthesis

Neural text to Speech (NTTS) synthesis is generated using deep learning and neural network techniques. The process of NTTS synthesis involves the following steps:

1. Text processing — The input text is processed to extract linguistic features, such as phonemes, syllables, and intonation patterns. This step involves tokenization, normalization, and linguistic analysis of the input text.
2. Acoustic modeling — The linguistic features are used to train an acoustic model, which is a neural network that maps the linguistic features to acoustic features, such as pitch, duration, and spectral envelope.
3. Waveform synthesis — The output of the acoustic model is used to generate the final speech waveform. This step involves applying signal processing techniques, such as vocoding and post-filtering, to convert the acoustic features into a natural-sounding speech signal.

NTTS synthesis can be trained on large datasets of speech and text data, which enables it to produce high-quality, natural-sounding speech output. NTTS synthesis can also be customized to produce different voices, accents, and languages, making it a versatile and powerful tool for various applications, including virtual assistants, audiobooks, and accessibility tools.

Differences between speech synthesizers and speech generators

The terms speech synthesizer and speech generator are often used interchangeably, but there are some differences between them. The difference between a speech synthesizer and a speech generator is primarily in their approaches to creating speech.

Speech synthesizer

A speech synthesizer is a device or software that takes a text input and generates an audible speech output that is typically computer-generated or synthetic. A speech synthesizer uses pre-recorded human speech or synthetic speech voice samples or mathematical models to generate speech output. The output can be highly customizable, allowing for the selection of different voices, accents, and languages.

Speech generator

On the other hand, a speech generator is a device or software that takes a text input and generates an audible speech output that is more similar to human speech from scratch using algorithms and machine learning models. A speech generator uses advanced techniques, such as deep learning and neural networks, to generate speech output that closely mimics human speech patterns, intonation, and emotion.

The difference

In essence, a speech synthesizer is designed to produce speech that is easily understandable, while a speech generator aims to produce speech that is not only understandable but also natural-sounding and expressive. While both technologies have their own advantages and limitations, the choice of technology depends on the specific application and the desired outcome.

Applications of speech generation technology

Speech generation technology has a wide range of applications in various industries, including but not limited to the following:

• Audiobooks and podcasts — Speech generation technology is commonly used to convert written text into spoken audio for audiobooks and podcasts, allowing listeners to enjoy content in an audio format.
• Apps — Speech generation technology can be integrated into various mobile and desktop applications to provide a more accessible and user-friendly experience for users.
• Telecommunication — Speech generation technology is used in automated call centers and interactive voice response (IVR) systems to provide automated assistance and improve customer service.
• Playback of synthesized speech — Synthesized speech can be played back in various applications, including virtual assistants and navigation systems, to provide audio instructions or information to users.
  
  

The #1 text to speech technology: Speechify

Speechify is a user-friendly text to speech tool that uses artificial intelligence and natural language processing to convert any physical or digital text into natural-sounding spoken words with the goal of making reading more accessible to people of all ages and abilities. The tool is perfect for those with physical disabilities or learning difficulties like vision impairments, dyslexia or ADHD or simply people who like to listen rather than read to become more productive and multitask.

The app can be used on a wide range of devices, including computers, smartphones, and tablets, allowing anyone to easily listen to content while on the go. Additionally, Speechify allows users to customize their reading experience by adjusting the speed and volume of the voice, choosing from a range of different voices and accents, and even highlighting text as it is being read aloud.

Whether you're a student, a professional, or just someone who loves to read, try Speechify for free and see how it can improve your reading experience.

FAQ

How can I embed TTS in apps?

To embed or integrate a TTS API in applications, developers can use markup languages like SSML to specify how the speech should be synthesized and played back.

How much does TTS cost?

Pricing for TTS services can vary depending on the provider and usage, but there are open-source options available for those on a budget. There are various apps and architectures used for speech generation, including open-source tools and proprietary toolkits like lPC.

How are speech generation tools trained?

At the core of speech generation are speech models, which are trained on a dataset of human voices. These models use deep neural networks to understand the phonemes, or distinct units of sound, that make up human speech. They then generate spectrograms, which represent the audio frequencies of the speech, and combine them with prosody, or the melody of speech, to create natural-sounding speech.

What is a vocoder?

A vocoder is an electronic device or software that analyzes the spectral characteristics of a human voice and applies those characteristics to a synthetic or electronic sound. Vocoder technology is widely used in music production, sound design, and voice processing.

How can I use speech to text?

Speech to text software transcribes speech data into text. For example, Automated speech recognition and transcription services can help automate the process of transcribing spoken words into text.