Emotive Text to Speech for Synthetic Voices

Emotion in text to speech is the single biggest factor in determining realism of AI voice over generators. In simpler words, it signifies the AI model’s capability to learn from human speech and imitate the conveyed emotions in the generated AI voice.

With recent advances in synthetic speech technology, it is now possible to express emotions like happiness, anger, sorrow, empathy, excitement, and many more in text to speech voices. According to a report published by Voices in 2017, a significant 77% of the spends on voice over jobs was allocated to entertainment and advertising industries, which require advanced capabilities to effectively portray emotions through voice.

Lack of emotiveness in text to speech has long been the biggest barrier for adoption in mainstream media applications. But this has seen some seminal breakthroughs in recent years, and now it is possible to create more engaging experiences using emotive AI voices.

Samples of Emotive Text to Speech

At Murf AI, we create AI-powered text to speech voices that go beyond communication to express contextual emotions. Listed below are some examples of emotive text to speech voices from Murf Studio.

To access the different styles for each voice on Murf Studio, simply click on the tab next to the voice with the default 'conversational' option and choose from the drop-down list based on your project needs. Currently, over 20 voices across different languages on Murf support multiple voice styles, including Miles, Ruby, Ken, and Ava.

The Emergence and Evolution of Text to Speech

In 1961, one of the earliest versions of computer-generated voices was created at Bell Labs. The base language it used was English—an IBM 704 computer was used to synthesize the lyrics to the song Daisy Bell and sing it using synthetic technology. It was a historic moment for speech synthesis; this clip was also featured in the screenplay of the novel 2001: A Space Odyssey.

While the need for using synthetic speech for emotive applications has always existed, text to speech systems in the past widely utilized synthetic voices to read aloud what is typed on the screen. This was primarily on account of the lack of emotive capabilities in the earlier versions. 

Recognizing the need for providing artificial voices that are more lifelike, modern TTS systems today focus on delivering text to speech with emotions using complex algorithms backed by artificial intelligence and natural language processing. It enables them to deliver lifelike text to speech that closely resembles human speech and makes listening to the output more engaging and realistic.

Technologies Used to Incorporate Emotion in Synthetic Speech

Deep Learning based models

This technique is one of the most recent or advanced methodologies for training speech models with emotional data. It uses deep neural networks (DNNs) at the core and is generally trained on custom recorded speech and corresponding script data in a labeled fashion. While these models understand contextual emotions to some extent, researchers have also experimented with training them on text data containing emotion labels. 

Hidden Markov Models 

Popularly referred to as HMMs, these models utilize statistical parameters to produce the most probable speech waveform. Key parameters, such as prosody, duration, and vocal chord frequencies, are typically incorporated. Although this method gained considerable traction among researchers, the emotional expressiveness it offers remains restricted compared to that achieved with deep learning models.

Articulatory Synthesis 

In traditional articulatory speech synthesis, the model simulates the movement of the tongue, lips, vocal cords, and other articulatory organs to generate speech sounds. This approach enables more precise control over speech parameters, resulting in higher-quality and more intelligible synthetic speech. By integrating emotional models into the articulatory speech system, the synthetic voice can dynamically adjust its articulatory movements and prosodic features to match the desired emotional expression.

Concatenative Speech Synthesis 

This technique combines pre-recorded segments of human speech, known as “units,” to generate emotionally expressive synthetic speech. To achieve emotional expressiveness, the database contains recordings of the same text spoken with various emotional states, such as happiness, sadness, anger, and others. These emotional variations are carefully labeled, allowing the system to search for the most suitable units based on the specified emotion.

Cross-Lingual Emotion Transfer in Synthetic Speech

Transferring emotions across languages is one of the most challenging problems with synthetic speech technologies. Each language has its own cultural nuances, and traditional localization techniques have been found ineffective in retaining the essence of the emotion while going from one language to another. 

The process involves two main steps: emotion embedding and voice synthesis. In the emotion embedding phase, a model is trained to map emotions from one language to another. This involves learning the cross-lingual emotional representations and identifying how emotional cues in one language can be transferred to another.

Once the emotion embedding is established, the voice synthesis phase takes over. During this stage, a text to speech (TTS) system generates speech using the input text and the target language while incorporating the transferred emotional features from the source language. By aligning the emotional characteristics of the two languages, the synthetic voice can accurately convey emotions across linguistic boundaries.

Use-Cases for Emotive TTS

The benefits of AI voice generators are tremendous, especially when the results have been enriched with human emotion. People who like listening to podcasts or audiobooks are the first to benefit. Even businesses can generate better user engagement by making their TTS voice overs more lifelike.

Emotive voices have widespread applications across various industries that can benefit from them:

eLearning

eLearning voiceovers are an important asset for learners as they help make learning flexible and versatile. Injecting the appropriate emotion through TTS technology imbues the right diction through realistic AI voices, which is required to make the course material more impactful, and aids retention and recall.

Listening to eLearning voiceovers that have the correct notes corresponding to human emotional speech makes the subject matter simulate the classroom environment when students listen to them. It also makes the course more engaging to listen to, helping boost attentiveness to what is being read.

Marketing and Advertising

Two industries that are perhaps leaders in applying TTS technology are marketing and advertising. There was a time when businesses were scurrying to robotize their operations; today, while that surge for automation still exists, businesses are looking to humanize their automated customer fronts.

They do this by applying emotion to voiceovers for advertising, using advanced TTS software that enables them to produce human-like voices to convey their intended message and establish a strong brand voice. With these tools, there is no need for voice actors.

Videos

Videos are by far the most engaging media that audiences like to consume, no matter the industry. Especially for those working in entertainment, it’s important to create videos at a steady pace with high-quality dubs.

It’s here that voice overs for YouTube videos shine best—by providing content creators with a highly expressive set of synthetic voices that enables them to get even more creative with the content they produce. It helps them make their videos with higher efficiencies using stored voice style.

Audiobooks and Podcasts

A natural process happens in the human mind when reading a book—it automatically emotes the words being read. This can be replicated through TTS modules as voiceovers for audiobooks to deliver a more immersive listening experience for the audience, much like they would feel when reading with the emotions in their own minds.

Speaking of podcasts, they’re simply a form of blog or conversations that are in audio format rather than written. Using expressive voice over for podcasts helps make them sound more humanized.

Best Text to Speech Software with Life Like Voices

The text to speech industry is teeming with software that provides lifelike synthesized voices with a variety of voice styles for various purposes. The leading six TTS solutions are listed below.

1. Murf AI

Murf is a powerful text to speech tool especially beneficial for creative voiceovers that need a lot of customizations.

It provides you with a set of pre-recorded realistic voices that are lifelike and of high quality. Businesses can leverage this tool to establish a consistent brand identity.

Features

• Text to speech using 120+ AI-generated voices close to likeness in human voice in over 20 languages

• Pitch, intonation, volume, emphasis, read speed, and pause adjustments.

• Script proofreading, background music, clip editing, and more.

Pros

• High customizability of your projects using voice adjustments

• Quick turnaround times

• Easy and simple interface

Pricing

Free plan available. Lite: $29 per user per month* , Plus: $49 per user per month* with an extensive feature list. 

*Check pricing page for the updated pricing information and more details.

2. Speechify

Speechify is your ready-to-go text to speech software that allows the conversion of any text into speech. It gives you the capability to add a TTS button to any app or website you are using for quick audio outputs.

Features

• Reading speed adjustments up to 5x

• Human-like AI voices that are high quality in over 30 languages

• Chrome extension available

Pros

• Speechify is a press-and-play TTS software, and it can be integrated with any screen from where you want the text read

• Easy to use

Pricing

A free package is available with 10 voices. You can sign up for $139 a year for premium.

3. Speechelo

Speechelo is one of the most straightforward text to speech tools for generating AI audio. It allows you to generate speech from text in just three steps. The platform is best suited for sales, training, and educational voiceover content creation.

Features

• Support for over 23 languages and 30 voices

• Online text editor available

• Breathing, speed, pitch adjustment, tone, and pause features are available.

Pros

• Speechelo is compatible with any kind of video creation tool.

• They provide a 60-day money-back guarantee.

Pricing

One-time payment purchase for $97—no free plan available.

4. Natural Reader

Natural Reader is an online text to speech tool for personal, commercial, and educational use. It supports over 20 types of text formats for easy audio conversions.

Features

• The commercial audio files are licensed for use on any public redistribution platforms.

• Emotions and voice effects

• Quick conversions through drag-and-drop features

Pros

It is cross-platform compatible, so you can log in through any device or channel with your user ID.

Pricing

You can download the software starting at $99.5 as a one-time payment. A free version is also available.

5. Azure Text to Speech

Azure Text to Speech is a voiceover generation tool by Microsoft that’s available to try for free for Azure users. The tool is highly technical and most suitable for business use cases.

Features

• Over 400 neural voices in 140 languages

• Rate, pitch, pauses, and pronunciation adjustments

• Deployed over the cloud, on-premises, or in containers

• Adds emotions to any AI voice

Pros

You can choose from several styles of speaking, like shouting, whispering, newscast, customer service, and more.

Pricing

Available on a pay-as-you-go basis.

6. Amazon Polly

Amazon Polly is a capable TTS that uses deep learning technology to generate humanlike speech. The platform is most suitable for enterprise-level use for creating speech-enabled applications.

Features

• Support for lexicons and SSML tags

• Adjustments for speaking style, pitch, volume, and rate

• Supports about 29 languages

Pros

The biggest advantage is that you get five million characters free every month for 12 months with Amazon Polly’s free plan.

Pricing

It’s a pay-as-you-go model.

Why Murf is the Best Text to Speech with Emotions?

When it comes to imbuing emotion into audio generated artificially, Murf is your best option because of two reasons:

• Murf Studio allows you to adjust not only the pitch and style of speaking but also control pauses and add emphasis to certain words or phrases. This helps create better outputs.

• An extensive library of realistic synthetic voices closes the gap between AI and real voices.

Murf has several other key features like use-case-based voices in countless accents to allow users further customizations.

Visit Murf to understand more amazing capabilities of this TTS tool!

Try Murf for Free

FAQs

What is the most realistic-sounding TTS?

Murf offers a plethora of AI-generated lifelike voices that are indistinguishable from real human voices.

How do I add emotions to text to speech?

This can be accomplished by using a TTS tool that allows you to select the emotion of the generated speech using several tools on the dashboard. Murf lets you effortlessly create lifelike audio with emotion.