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Text to speech conversion software

Technology category · O*NET

Text to speech conversion software is a technology category in the O*NET database. Across U.S. occupations, 2 report using software or tools in this category. The named products below are the specific examples O*NET records for those jobs.

A Hot tag marks technologies O*NET sees frequently in employer job postings; In demand marks tools an occupation specifically requires.

Example software & tools

Ranked by how many occupations list each product. Each number is an occupation count — a job is counted once per product — so the product rows overlap and do not sum to the category total.

Software / tool Occupations Tags
Text to speech software 2

Occupations that use Text to speech conversion software

How AI is used by roles that use Text to speech conversion software

A software category is not itself "being automated" — but we can look at the roles that report using Text to speech conversion software and ask how those people actually use AI. This rolls the Anthropic Economic Index per-role signal up across those roles, weighted by how much observed AI activity each one has. 100.0% of the 2 roles that use this category carry observed AI-usage data (2 roles).

Across those roles, 46.2% of AI conversations are people working with AI and 50.1% hand a task to AI , with an average autonomy of 4.00 / 5.

Collaboration pattern Share What it means
directive 49.2% AI does it; you give the instruction
task iteration 43.4% you and AI go back and forth
learning 1.9% you ask AI to explain or teach
validation 1.0% you do it; AI checks your work
feedback loop 0.9% AI does it, then adjusts from your feedback

Roles behind this signal

The roles using this category that have the most AEI data. "Works with AI" is the role's share of conversations that augment rather than automate.

Occupation Works with AI Autonomy
Poets, Lyricists and Creative Writers 46.2% 4.0/5
Speech-Language Pathology Assistants

Source: Anthropic Economic Index (2026-01-15-v4-plus-2025-03-27-v2) over a sample of Claude.ai Free and Pro conversations — not all AI tools and not the whole workforce. Roles list software categories in O*NET; this does not mean AI is used inside Text to speech conversion software, only that people in those roles use AI. Some conversations are left unclassified, so shares need not sum to 100.

Industries that concentrate this

Where Text to speech conversion software matters most across the economy. Employment reach is the share of an industry's workers in occupations that significantly use Text to speech conversion software (O*NET importance ≥ 3 of 5, or report using the tool category). Concentration compares that reach to the national average industry, so a value above 1× means the requirement is more pervasive here than across the economy as a whole.

Nationally, about 0.1% of workers are in occupations that significantly use Text to speech conversion software (measured across 34 industries).

Sectors with the most such workers

Sector Workers Employment reach
Health Care and Social Assistance 61,620 0.3%
Educational Services 16,500 0.1%
Professional, Scientific, and Technical Services 15,120 0.1%
Information 12,010 0.4%
Administrative and Support and Waste Management and Remediation Services 6,330 0.1%
Arts, Entertainment, and Recreation 5,360 0.2%
Management of Companies and Enterprises 2,670 0.1%
Retail Trade 2,650 0.0%
Other Services (except Public Administration) 2,590 0.1%
Finance and Insurance 1,870 0.0%
Wholesale Trade 1,210 0.0%
Manufacturing 950 0.0%

Industries where it is most concentrated

Industry Level Concentration Employment reach
Information Sector 0.4%
Health Care and Social Assistance Sector 0.3%
Arts, Entertainment, and Recreation Sector 0.2%
Educational Services Sector 0.1%
Professional, Scientific, and Technical Services Sector 0.1%
Administrative and Support and Waste Management and Remediation Services Sector 0.1%

Reach is a measure of how widespread a requirement is across an industry's workforce, not how intensively any individual uses it. Sector worker counts come from BLS OEWS employment; the significance threshold and tool use come from O*NET. Industries shown by concentration are filtered to a real worker base so a tiny specialty cannot top the list on rounding.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 3, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Text to speech conversion software." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026. https://singulariki.com/tools/text-to-speech-conversion-software

APA

Singulariki. (2026). Text to speech conversion software. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tools/text-to-speech-conversion-software

BibTeX
@misc{singulariki-text-to-speech-conversion-software,
  title  = {Text to speech conversion software},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026},
  url    = {https://singulariki.com/tools/text-to-speech-conversion-software}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.