The global voice cloning market was worth USD 0.97 billion in 2023. The global market is predicted to reach USD 1.27 billion in 2024 and USD 10.81 billion by 2032, growing at a CAGR of 30.70% during the forecast period.
Voice cloning is a technique that makes it easier to narrate audiobooks and adds a familiar voice for handling instructions. It allows customers to produce a computer version of their voice at minimal cost and a fraction of the time compared to creating conventional text-to-speech voices. Voice cloning technology combined with artificial intelligence helps improve the convertibility of chatbots and voice assistants. Businesses focus on improving the customer experience by presenting a familiar voice on their products and services. By providing a significantly better customer experience using these solutions, businesses can build meaningful long-term customer relationships. Technology providers are also adopting advanced technologies to develop effective voice cloning solutions. For instance, in 2019, Deepsync Technologies, a tech startup in India, used artificial intelligence to create audio content via voice cloning.
A voice cloning procedure usually requires a few hours of recorded speech to create a data set, which is then used to form a new model. With the increasing acceptance of machine learning and artificial intelligence solutions, developers are working to reduce the time required to complete a voice cloning process. For example, in 2019, a new Github project introduced a real-time voice cloning toolkit that enables the user to clone a voice in less than five seconds of audio sampling.
However, the complexity of recreating natural speech will hamper market growth in the future. Nonetheless, integrating artificial intelligence technologies in voice cloning services and personalization in human-team interaction will shortly offer lucrative avenues for players in the voice cloning market. This, in turn, will help overcome the market's obstacles in the next two years.
The massive popularity of chatbots and virtual assistants worldwide and new product innovations introduced by industry giants will open new growth prospects for the voice cloning market in the coming years. The increased demand for new voice technologies in telecommunications, banking, media and entertainment, education, defense and energy, and public services sectors, among others, will not only fuel market growth but will take voice cloning activities to new heights.
The voice cloning solutions segment has experienced considerable growth in recent years due to the increasing adoption of cloned voice services in education, healthcare, BFSI, media and entertainment, sales retail, and other potential industries. CereProc, a voice cloning technology provider, developed CereVoice Me, an online voice cloning solution that can generate a computer version of a user’s voice. The developers of this cutting-edge solution have streamlined the process of creating text-to-speech from CereProc, allowing users to make recordings in their homes in just a few hours.
These voice cloning methods require many recorded voices and extensive post-production. Although they produce results, they are not cost-effective and also time-consuming, acting as a challenger for those looking for a TTS voice that looks like a cloned voice. Various technology providers are making voice cloning accessible to potential end users. These solutions are particularly useful for voice banking services. Voice cloning tools can be helpful in various degenerative diseases, such as motor neuron disease (MND) and amyotrophic lateral sclerosis (ALS). These tools can also be helpful for critical operations, such as laryngectomy, which can lead to loss of speech. Patients can use a voice-generating tool to hear their voices, which have been cloned from their previously recorded voices. These emerging technology solutions drive growth in this segment during the forecast period.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2032 |
Base Year |
2023 |
Forecast Period |
2024 to 2032 |
CAGR |
30.7% |
Segments Covered |
By Component, Deployment Mode, Application, End-User Industry, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
Google, Microsoft, IBM Corporation, AT&T Corp., Baidu, Nuance Communications, CereProc, Lyrebird, Kata.ai, Alt Inc., Aristech GmbH, Acapela Group, and Others. |
The voice cloning market is segmented into solutions and services, with solutions still sub-segmented into tools and software platforms. Of these, the solutions segment is likely to develop with a considerable CAGR in the coming years.
According to the application, the market is divided into chatbots and assistants, digital games, accessibility, interactive games, and more, including ad systems, talking avatars, and text readers.
The end-user segment of the market is separated into health and life sciences, telecommunications, travel and hospitality, BFSI, energy and public services, government, defense, education, and media and entertainment.
North America has shown wide acceptance of voice cloning solutions compared to other regions. Many suppliers and industry participants in North America are involved in innovation and new product development. These companies also plan to integrate AI capabilities into voice cloning solutions to implement more natural voice cloning samples.
The major companies operating in the global voice cloning market include Google, Microsoft, IBM Corporation, AT&T Corp., Baidu, Nuance Communications, CereProc, Lyrebird, Kata.ai, Alt Inc., Aristech GmbH and Acapela Group.
In April 2020, Lovo, Inc., an artificial intelligence voice-over platform developed by a team of experts in machine learning as well as artificial intelligence from the University of California at Berkeley, introduced a human voice-over platform to assist in education, marketing, entertainment, and other audio content.
In May 2020, Resemble AI, an AI solutions company known for creating cloned voices, announced a Unity plugin that allows game developers to add dynamically created voices with voice cloning. The company's Unity plugin extends Resemble Clone, a product that allows users to record a few sentences in their voices and immediately generate high-quality samples.
By Component
By Deployment
By Application
By End User Industry
By Region
North America
The United States
Canada
Rest of North America
Europe
The United Kingdom
Spain
Germany
Italy
France
Rest of Europe
The Asia Pacific
India
Japan
China
Australia
Singapore
Malaysia
South Korea
New Zealand
Southeast Asia
Latin America
Brazil
Argentina
Mexico
Rest of LATAM
The Middle East and Africa
Saudi Arabia
UAE
Lebanon
Jordan
Cyprus
Frequently Asked Questions
Voice cloning technologies find significant adoption in industries such as entertainment, where it is used for dubbing and creating realistic virtual characters. Additionally, customer service, healthcare, and education sectors are increasingly integrating voice cloning for enhanced user experiences and efficiency.
The Voice Cloning Market is actively addressing security concerns through the development of robust authentication mechanisms and encryption protocols. Industry stakeholders are collaborating with cybersecurity experts to ensure the responsible and ethical use of voice cloning technologies.
Artificial intelligence is a cornerstone in the development of voice cloning solutions globally. AI-powered algorithms enable the creation of highly realistic and natural-sounding voices by analyzing extensive datasets. Continuous advancements in AI contribute to the improvement of voice cloning accuracy and quality.
Advancements in deep learning techniques, particularly in neural network architectures, significantly impact the Voice Cloning Market. These advancements contribute to the development of more sophisticated voice cloning models, resulting in improved accuracy, naturalness, and adaptability across diverse linguistic nuances.
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