Google Cloud Text-to-Speech
Google Cloud Text-to-Speech enables developers to convert text to audio by applying powerful neural network models.
Market Share of Google Cloud Text-to-Speech
Current Customer(s)
73
Market Share (Est.)
1.42%
Ranking
#12
Top Competitors and Alternatives of Google Cloud Text-to-Speech
The top three of Google Cloud Text-to-Speech’s competitors in the NLP And Text Analytics category are Hugging Face with 33.78%, GitHub Copilot with 8.71%, Dragon NaturallySpeaking with 6.53% market share.
Popular Comparisons
Top Competitors and Alternatives of Google Cloud Text-to-Speech
The top three of Google Cloud Text-to-Speech’s competitors in the NLP And Text Analytics category are Hugging Face with 33.78%, GitHub Copilot with 8.71%, Dragon NaturallySpeaking with 6.53% market share.
Google Cloud Text-to-Speech vs Hugging Face
Google Cloud Text-to-Speech vs GitHub Copilot
Google Cloud Text-to-Speech vs Dragon NaturallySpeaking
Google Cloud Text-to-Speech vs IBM Watson Assistant
Google Cloud Text-to-Speech vs Azure Translator
Google Cloud Text-to-Speech vs Microsoft Azure Speech to Text
Google Cloud Text-to-Speech vs Azure Language Understanding
Google Cloud Text-to-Speech vs Google Cloud Speech-to-Text
Customers of Google Cloud Text-to-Speech
Around the world in 2025, over 73 companies have started using Google Cloud Text-to-Speech as NLP And Text Analytics tool.
| Customers | Employee Range | City | Region | Country | Social Links |
|---|---|---|---|---|---|
| EPAM | 10,000+ | Newtown | Pennsylvania | United States |     |
| University Of Waterloo | 10,000+ | Waterloo | Ontario | Canada | |
| ING Groep NV | 10,000+ | Amsterdam | North Holland | Netherlands | |
| Transdev | 10,000+ | Issy-les-Moulineaux | Ile-de-France | France | |
| IBM | 10,000+ | Armonk | New York | United States | |
| XPO | 10,000+ | Greenwich | Connecticut | United States | |
| NCR Voyix | 10,000+ | Atlanta | Georgia | United States | |
| Atos | 10,000+ | Bezons | Ile-de-France | France | |
| TIBCO Software | 10,000+ | Palo Alto | California | United States | |
| Accenture | 10,000+ | Dublin | Leinster | Ireland | |
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Google Cloud Text-to-Speech Customers by Products and Services
The top three products and services offering customers that use Google Cloud Text-to-Speech for NLP And Text Analytics are Cloud Services (6), Artificial Intelligence (5), Technology (4).
Customers
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Google Cloud Text-to-Speech Customers by Employee Size
The majority of Google Cloud Text-to-Speech's customers for the nlp-and-text-analytics category fall in the company size of 10,000+ employees (14 companies), 100 - 249 employees (14 companies), 1,000 - 4,999 employees (11 companies).
Employee Size
Google Cloud Text-to-Speech Customers by Geography
The top three geographies of Google Cloud Text-to-Speech for nlp-and-text-analytics are the United States with 26(42.62%), India with 13(21.31%), United Kingdom with 5(8.20%) customers respectively.
Customers
Employees of Google Cloud Text-to-Speech
Also see other Products/Services by Google Cloud Text-to-Speech in:
FAQ
Find answers to the most often asked questions by users.
Who are the top Google Cloud Text-to-Speech competitors?
Google Cloud Text-to-Speech’s Top competitors in the nlp-and-text-analytics category are Hugging Face, GitHub Copilot, Dragon NaturallySpeaking. You can view a full list of Google Cloud Text-to-Speech competitors here. 6sense uses advanced data mining and AI algorithms to track customers and competitors of Google Cloud Text-to-Speech and 40,000 other technologies on the internet. You can also compare Google Cloud Text-to-Speech and its feature with top competitors here : Google Cloud Text-to-Speech vs Hugging Face Google Cloud Text-to-Speech vs GitHub Copilot Google Cloud Text-to-Speech vs Dragon NaturallySpeaking.
What is Google Cloud Text-to-Speech customer distribution based on company size?
What is Google Cloud Text-to-Speech market share in the nlp-and-text-analytics?
What are the top countries that use Google Cloud Text-to-Speech?
What are the top industries that use Google Cloud Text-to-Speech?
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