The Ultimate Guide to Speech Synthesis

Speech synthesis is an intriguing area of artificial intelligence (AI) that’s been extensively developed by major tech corporations like Microsoft, Amazon, and Google Cloud. It employs deep learning algorithms, machine learning, and natural language processing (NLP) to convert written text into spoken words.

Basics of Speech Synthesis

Speech synthesis, also known as text-to-speech (TTS), involves the automatic production of human speech. This technology is widely used in various applications such as real-time transcription services, automated voice response systems, and assistive technology for the visually impaired. The pronunciation of words, including “robot,” is achieved by breaking down words into basic sound units or phonemes and stringing them together.

Three Stages of Speech Synthesis

Speech synthesizers go through three primary stages: Text Analysis, Prosodic Analysis, and Speech Generation.

1. Text Analysis: The text to be synthesized is analyzed and parsed into phonemes, the smallest units of sound. Segmentation of the sentence into words and words into phonemes happens in this stage.
2. Prosodic Analysis: The intonation, stress patterns, and rhythm of the speech are determined. The synthesizer uses these elements to generate human-like speech.
3. Speech Generation: Using rules and patterns, the synthesizer forms sounds based on the phonemes and prosodic information. Concatenative and unit selection synthesizers are the two main types of speech generation. Concatenative synthesizers use pre-recorded speech segments, while unit selection synthesizers select the best unit from a large speech database.

Most Realistic TTS and Best TTS for Android

While many TTS systems produce high quality and realistic speech, Google’s TTS, part of the Google Cloud service, and Amazon’s Alexa stand out. These systems leverage machine learning and deep learning algorithms, creating seamless and almost indistinguishable-from-human speech. The best TTS engine for Android smartphones is Google’s Text-to-Speech, with a wide range of languages and high-quality voices.

Best Python Library for Text to Speech

For Python developers, the gTTS (Google Text-to-Speech) library stands out due to its simplicity and quality. It interfaces with Google Translate’s text-to-speech API, providing an easy-to-use, high-quality solution.

Speech Recognition and Text-to-Speech

While speech synthesis converts text into speech, speech recognition does the opposite. Automatic Speech Recognition (ASR) technology, like IBM’s Watson or Apple’s Siri, transcribes human speech into text. This forms the basis of voice assistants and real-time transcription services.

Pronunciation of the word “Robot”

The pronunciation of the word “robot” varies slightly depending on the speaker’s accent, but the standard American English pronunciation is /ˈroʊ.bɒt/. Here is a breakdown:

• The first syllable, “ro”, is pronounced like ‘row’ in rowing a boat.
• The second syllable, “bot”, is pronounced like ‘bot’ in ‘bottom’, but without the ‘om’ part.

Example of a Text-to-Speech Program

Google Text-to-Speech is a prominent example of a text-to-speech program. It converts written text into spoken words and is widely used in various Google services and products like Google Translate, Google Assistant, and Android devices.

Best TTS Engine for Android

The best TTS engine for Android devices is Google Text-to-Speech. It supports multiple languages, has a variety of voices to choose from, and is natively integrated with Android, providing a seamless user experience.

Difference Between Concatenative and Unit Selection Synthesizers

Concatenative and unit selection are two main techniques employed in the speech generation stage of a speech synthesizer.

1. Concatenative Synthesizers: They work by stitching together pre-recorded samples of human speech. The recorded speech is divided into small pieces, each representing a phoneme or a group of phonemes. When a new speech is synthesized, the appropriate pieces are selected and concatenated together to form the final speech.
2. Unit Selection Synthesizers: This approach also relies on a large database of recorded speech but uses a more sophisticated selection process to choose the best matching unit of speech for each segment of the text. The goal is to reduce the amount of ‘stitching’ required, thus producing more natural-sounding speech. It considers factors like prosody, phonetic context, and even speaker emotion while selecting the units.

Top 8 Speech Synthesis Software or Apps

1. Google Text-to-Speech: A versatile TTS software integrated into Android. It supports different languages and provides high-quality voices.
2. Amazon Polly: An AWS service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice.
3. Microsoft Azure Text to Speech: A robust TTS system with neural network capabilities providing natural-sounding speech.
4. IBM Watson Text to Speech: Leverages AI to produce speech with human-like intonation.
5. Apple’s Siri: Siri isn’t only a voice assistant but also provides high-quality TTS in several languages.
6. iSpeech: A comprehensive TTS platform supporting various formats, including WAV.
7. TextAloud 4: A TTS software for Windows, offering conversion of text from various formats to speech.
8. NaturalReader: An online TTS service with a range of natural-sounding voices.