Custom Vocabulary for Programming: APIs, Frameworks & Libraries
Set up custom programming vocabulary for accurate code dictation. Framework names, API terms, and library names transcribed correctly with Sonicribe.
Sonicribe Team
Product Team

Table of Contents
Programming Vocabulary Is the Key to Accurate Developer Dictation
Programming terminology is a minefield for general speech recognition. Framework names like "Nuxt" sound like "next" or "nuts." Library names like "tRPC" become "TRP see." API methods like "addEventListener" turn into word salad. Without custom vocabulary, dictating technical content is an exercise in frustration.
The solution is straightforward: teach your dictation tool the exact terms you use. Sonicribe's custom vocabulary system, combined with its pre-built developer vocabulary pack, lets you dictate code comments, documentation, commit messages, PR descriptions, AI prompts, and technical discussions with accuracy that matches your typing.
This guide provides ready-to-use vocabulary lists for the most popular programming ecosystems and shows you how to build a custom vocabulary tailored to your specific stack.
Why Developers Need Custom Vocabulary
The Technical Language Problem
Programming terminology is hostile to speech recognition for several reasons:
Compound words and camelCase. "addEventListener," "getElementById," "useCallback" -- these are not in any dictionary. They are programmer-created compounds that speech recognition has never encountered. Acronyms everywhere. API, SDK, CLI, CI/CD, DNS, SQL, REST, gRPC, JWT, CORS, HTTPS -- developers communicate in acronyms that speech recognition may expand incorrectly or not recognize at all. Brand names and invented words. Kubernetes, Terraform, Zustand, Drizzle, Prisma, Zod -- these are invented names with no phonetic precedent in natural language. Version numbers and symbols. "React 19," "Node.js 22," "Python 3.12" -- mixing words with version numbers confuses many speech recognition systems. Homophones with different meanings. "Cache" vs. "cash," "byte" vs. "bite," "route" vs. "root" -- context-dependent homophones require vocabulary guidance.Common Misrecognitions
| You Say | Without Vocabulary | With Vocabulary |
|---|---|---|
| Kubernetes | "Cooper Netties" | "Kubernetes" |
| tRPC | "T R P C" or "trip see" | "tRPC" |
| Zustand | "zoo stand" | "Zustand" |
| GraphQL | "graphic well" | "GraphQL" |
| WebSocket | "web sock it" | "WebSocket" |
| PostgreSQL | "post gress sequel" | "PostgreSQL" |
| npm install | "N P M install" | "npm install" |
| useState | "use state" | "useState" |
| middleware | "middle wear" | "middleware" |
Sonicribe's Developer Vocabulary Pack
Sonicribe includes a pre-built developer vocabulary pack covering common programming terms. Install it as your baseline. The pack includes:
- Major programming language names and versions
- Popular framework and library names
- Common CLI tools and package managers
- Database technology names
- Cloud platform terminology
- DevOps and CI/CD terms
- Web standards and protocol names
- Common design pattern terminology
Building Your Stack-Specific Vocabulary
JavaScript and TypeScript Ecosystem
Core language terms:useState, useEffect, useCallback, useMemo, useRef, useContext, useReducer, Promise, async/await, EventListener, querySelector, createElement, appendChild, innerHTML, className, classList, setTimeout, setInterval, localStorage, sessionStorage, fetch, XMLHttpRequest
React ecosystem:React, Next.js, Remix, Gatsby, React Router, React Query, TanStack Query, Zustand, Jotai, Recoil, Redux Toolkit, Framer Motion, Radix UI, shadcn/ui, Headless UI, React Hook Form, Zod, Yup
Vue ecosystem:Vue, Nuxt, Pinia, Vuex, Vue Router, Vuetify, Quasar, PrimeVue, VueUse, Vite, Vitest
Svelte ecosystem:Svelte, SvelteKit, Svelte Store, Svelte Actions, skeleton
Build and tooling:Vite, webpack, Turbopack, esbuild, SWC, Rollup, Parcel, Babel, TypeScript, TSConfig, ESLint, Prettier, Biome, pnpm, yarn, Bun, Deno
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Vitest, Jest, Playwright, Cypress, Testing Library, Storybook, Chromatic
Python Ecosystem
Core language:def, class, self, __init__, __name__, __main__, lambda, comprehension, generator, decorator, asyncio, typing, dataclass, Pydantic, Protocol
Web frameworks:Django, Flask, FastAPI, Starlette, SQLAlchemy, Alembic, Celery, Gunicorn, Uvicorn, ASGI, WSGI
Data science and ML:pandas, NumPy, scikit-learn, matplotlib, seaborn, Plotly, Jupyter, TensorFlow, PyTorch, Keras, transformers, Hugging Face, LangChain, LlamaIndex, OpenAI API
Tools:Poetry, pip, conda, virtualenv, pyenv, Ruff, Black, mypy, pytest, tox, nox, pre-commit
Go Ecosystem
goroutine, channel, interface, struct, defer, panic, recover, Gin, Echo, Fiber, GORM, sqlx, cobra, viper, protobuf, gRPC
Rust Ecosystem
cargo, crate, impl, trait, enum, match, Option, Result, unwrap, async/await, Tokio, Actix, Axum, Serde, Diesel, SQLx, clippy, rustfmt
Infrastructure and DevOps
Containers and orchestration:Docker, Dockerfile, docker-compose, Kubernetes, kubectl, Helm, Istio, Envoy, containerd, Podman
Cloud platforms:AWS, GCP, Azure, Vercel, Netlify, Cloudflare Workers, Fly.io, Railway, Render, DigitalOcean, Supabase, PlanetScale, Neon
CI/CD:GitHub Actions, GitLab CI, CircleCI, Jenkins, Argo CD, Terraform, Pulumi, Ansible, CloudFormation
Monitoring and observability:Datadog, Grafana, Prometheus, New Relic, Sentry, OpenTelemetry, PagerDuty, Jaeger
Database Technologies
PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Cassandra, DynamoDB, CockroachDB, TimescaleDB, ClickHouse, Elasticsearch, Pinecone, Weaviate, Chroma, Qdrant, Prisma, Drizzle, TypeORM, Sequelize, Knex
Configuring Smart Replacements for Code
Smart replacements turn spoken phrases into code patterns:
| You Say | Sonicribe Types |
|---|---|
| "arrow function" | "() => {}" |
| "async arrow" | "async () => {}" |
| "console log" | "console.log()" |
| "use state hook" | "const [, set] = useState()" |
| "try catch block" | "try {\n\n} catch (error) {\n\n}" |
| "import from" | "import {} from ''" |
| "export default" | "export default" |
| "null check" | "if (value !== null && value !== undefined)" |
These replacements are most useful when dictating code directly. For documentation and communication dictation, you may want to keep them disabled and enable them only when working in code mode.
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Dictation Workflows for Developers
Documentation and Comments
The primary dictation use case for developers. Speak your documentation naturally:
"This function accepts a user ID as a string parameter and returns a Promise that resolves to a User object or null if the user is not found. It queries the database using the Prisma client and includes the user's profile and settings relations. Throws a DatabaseError if the connection fails."
Custom vocabulary ensures "Prisma," "DatabaseError," and "Promise" are transcribed correctly.
AI Coding Prompts
When working with Copilot, Cursor, or other AI assistants, dictate detailed prompts:
"Write a TypeScript function that accepts an array of Product objects and groups them by category. Each category should map to an array of products sorted by price ascending. Use a Map for the grouping and return the Map. Include JSDoc comments and handle the edge case of an empty input array."
This detailed prompt takes 15 seconds to dictate versus 45 to 60 seconds to type.
Commit Messages and PR Descriptions
Dictate descriptive commit messages and PR descriptions:
"Refactor the authentication middleware to use the new JWT validation library. This replaces the deprecated jsonwebtoken package with jose, which supports the latest JWT standards and has better TypeScript types. All existing tests pass with the new implementation. Added additional tests for token expiration and invalid signature handling."
Slack and Team Communication
Technical discussions with teammates flow naturally through dictation:
"I looked into the performance issue with the dashboard query. The problem is that we are doing N plus one queries when loading the user's projects. I have a fix using Prisma's include with a select to load only the fields we need. This drops the query count from 47 to 3 and reduces load time from 1.2 seconds to 180 milliseconds. PR is up for review."
Privacy for Proprietary Code
Developers working on proprietary software, pre-release features, or confidential projects should be cautious about cloud-based dictation. Your spoken descriptions of architectures, algorithms, and product features contain commercially sensitive information.
Sonicribe processes all audio locally on your Mac. Your code descriptions, architecture discussions, and technical documentation never leave your machine. This is critical for developers at companies with strict IP protection policies.
This privacy applies to every dictation workflow: documentation dictated into VS Code, prompts sent to AI assistants, commit messages, PR descriptions, Slack messages, and code review comments. Nothing leaves your device at any point.
Voice Dictation for Code Reviews
Code reviews involve significant written communication: explaining your reasoning for requested changes, providing context on alternative approaches, and asking clarifying questions about implementation decisions. Voice dictation makes thorough code reviews faster:
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"I noticed that this function is doing both validation and transformation in a single pass. Consider splitting it into two separate functions: one that validates the input and returns either an error or the validated data, and a second that transforms the validated data into the output format. This makes each function easier to test independently and follows the single responsibility principle. The transformation logic in particular would benefit from its own unit tests since the business rules here are likely to change as we add new product types."
This detailed, constructive review comment took 25 seconds to dictate. Typing it would take over a minute, which means many developers would write a shorter, less helpful comment instead.
Maintaining Your Developer Vocabulary
Technology evolves rapidly. New frameworks, libraries, and tools emerge constantly. Maintain your vocabulary:
Monthly review: Spend five minutes adding any new tools or technologies you have started using. Project kickoff: When starting a new project, add the project-specific package names, API endpoint names, and domain terminology. Team sharing: If your team adopts Sonicribe, maintain a shared vocabulary list that covers your common stack. Each team member adds their specific additions on top.Privacy for Developer Workflows
Developers working on proprietary software, pre-release features, or confidential projects face real risks with cloud-based dictation. When you speak about your architecture, describe an algorithm, or dictate a prompt that includes proprietary business logic, that audio contains intellectual property. Cloud services process this audio on external servers where it may be logged, stored, or used for model training.
Sonicribe processes all audio on your Mac. No server receives your spoken descriptions of code, architecture, or product features. For developers at startups protecting pre-launch IP, enterprise teams under NDA, or open-source contributors working on security-sensitive projects, this is a meaningful safeguard.
This privacy applies to every dictation workflow: documentation dictated into VS Code, prompts sent to AI assistants, commit messages, PR descriptions, Slack messages, and code review comments all stay on your device.
Accuracy Benchmarks for Developer Content
With the developer vocabulary pack installed and your stack-specific terms added, here are realistic accuracy expectations:
| Content Type | Expected Accuracy | Notes |
|---|---|---|
| English documentation prose | 97-99% | Natural language with technical nouns |
| Code comments | 95-98% | Mix of natural language and technical terms |
| AI coding prompts | 96-99% | Natural language descriptions of code requirements |
| Commit messages | 97-99% | Short, structured technical descriptions |
| Slack/team messages | 97-99% | Conversational with technical vocabulary |
| Pure code dictation | 85-92% | Syntax-heavy content remains challenging |
The key insight is that the most valuable developer dictation use cases -- documentation, AI prompts, and communication -- are the ones where accuracy is highest. Pure code dictation remains the weakest use case, which is why the hybrid voice-plus-keyboard approach is recommended.
The Cost Advantage for Developer Teams
Developer tools subscriptions add up. IDE licenses, cloud services, monitoring tools, and SaaS platforms consume significant budget. Sonicribe's one-time $79 price is refreshingly simple:
| Tool | Pricing Model | Annual Cost per Developer |
|---|---|---|
| Sonicribe | $79 one-time | $79 total (year 1), $0 (year 2+) |
| GitHub Copilot | $19/month | $228/year |
| Otter.ai Business | $20/month | $240/year |
| Dragon Professional | $699 one-time | $699 total |
Sonicribe complements tools like Copilot rather than replacing them. Use Sonicribe to dictate the prompts that make Copilot more effective. The combination produces better code faster than either tool alone.
Getting Started
1. Download Sonicribe and install the Large v3 Turbo model
2. Install the Developer vocabulary pack (immediate baseline improvement)
3. Add your stack-specific terms from the lists above (10 minutes)
4. Configure smart replacements for your most common code patterns
5. Start with documentation and communication before attempting code dictation
6. Expand gradually as you develop your dictation muscle memory
Your voice is faster than your keyboard for documentation, communication, and AI prompts. Sonicribe's custom vocabulary ensures that your technical language is transcribed with the precision your code demands.
Download Sonicribe and start dictating technical content accurately. $79 one-time, offline, and built for developers.Related Reading
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