Open Source Speech Recognition: The Transparency Advantage

When you speak your most intimate thoughts to a diary app, how do you know what happens to your voice? With proprietary speech recognition, you're trusting a black box. With open-source technology like Sherpa ONNX, you can actually verify the code processing your words.

The Black Box Problem

Most voice diary apps use proprietary speech recognition from Google, Amazon, Apple, or Microsoft. These systems are incredibly sophisticated, built by world-class engineers, and generally very accurate. But they share one critical limitation: you cannot see what they're actually doing.

When you speak to a proprietary voice system, your audio passes through layers of code you cannot examine. You must trust that the company is doing what they claim. You must believe their privacy policy. You must hope their security is as robust as they promise. But you cannot verify any of this independently.

Trust Without Verification

This "trust us" approach dominates consumer technology. Companies ask you to believe they're protecting your privacy, securing your data, and not using your information in ways you wouldn't approve. Sometimes they deserve that trust. Sometimes they violate it spectacularly.

Recent history is filled with privacy scandals where companies promised protection but secretly collected data, shared information with third parties, or suffered breaches they initially concealed. Users discovered these violations only after journalists, whistleblowers, or regulators exposed them.

Open Source: Trust Through Verification

Open source software operates on a different principle: don't trust, verify. The source code is publicly available for anyone to examine. Security researchers can audit it for vulnerabilities. Privacy advocates can confirm data handling practices. Experts can verify that the software actually does what it claims.

This transparency doesn't just benefit experts. When independent researchers audit open source code and find no privacy violations or security flaws, everyone benefits from that verification. You don't need to personally review the code to benefit from the fact that hundreds of other qualified people can and do.

Sherpa ONNX: Open Source Speech Recognition

Hello Diary uses Sherpa ONNX for speech recognition. This is an open source project that converts spoken words to text entirely on your device. The entire codebase is publicly available on GitHub. Anyone can download it, examine it, compile it, and verify exactly what it does.

How Sherpa ONNX Works

Sherpa ONNX uses neural network models trained on public speech datasets. These models run locally on your device, processing audio in real-time without internet connection. The models are mathematical transformations that convert audio patterns into text predictions. There are no secret algorithms, hidden data collection, or mysterious processing steps.

Because the code is open, researchers have verified that audio never leaves your device during processing. There are no network calls, no logging to remote servers, no data transmission. The verification is mathematical: trace the code from audio input to text output, and confirm no data exits the system.

The Security Advantage

Open source software often proves more secure than proprietary alternatives. This seems counterintuitive. If attackers can see the code, won't they find vulnerabilities more easily? In practice, the opposite occurs.

Linus's Law: Many Eyes Make Bugs Shallow

Open source benefits from a security principle called Linus's Law: given enough eyeballs, all bugs are shallow. When thousands of developers can examine code, security vulnerabilities get discovered and fixed quickly. Contrast this with proprietary software where only company employees review the code, and vulnerabilities may lurk for years.

Major open source projects like Linux, Firefox, and Signal demonstrate this advantage. They undergo constant security auditing by independent researchers. When vulnerabilities are found, they're disclosed responsibly and patched rapidly. The transparency creates accountability.

No Security Through Obscurity

Proprietary software often relies on "security through obscurity"—keeping the system secret to prevent attacks. But this approach fails when determined attackers reverse-engineer the software, when employees leak code, or when breaches expose systems. True security comes from strong cryptography, robust architecture, and audited code that remains secure even when fully exposed.

Community Trust and Development

Open source projects build differently than proprietary software. Instead of a company making decisions behind closed doors, development happens in public. Feature discussions, bug reports, and code changes are visible to everyone.

This transparency creates accountability. Developers cannot secretly add telemetry, backdoors, or privacy-violating features without community notice. Every code change goes through public review before acceptance. This collaborative oversight protects users in ways corporate governance never can.

Comparing Open and Closed Speech Recognition

Let's examine the practical differences between open and proprietary speech recognition for privacy-critical applications like journaling.

Three Critical Differences

Data Flow Verification

With proprietary APIs, you trust the policy. With open source, you verify the code. You can mathematically prove audio never leaves your device.

Model Training Transparency

Proprietary models train on secret datasets. Open source models uses public datasets. You can see exactly what data trained the models and understand potential biases.

Update Trust

Proprietary updates happen in the dark. Open source updates are public code changes. If an update added privacy-violating features, it would be immediately visible.

Performance: Open Source Can Compete

A common misconception suggests open source software is inferior to proprietary alternatives. For speech recognition specifically, modern open source has reached remarkable quality.

Sherpa ONNX achieves accuracy comparable to commercial systems for many use cases. For diary journaling—where perfect transcription matters less than privacy—open source delivers more than adequate performance while offering superior privacy guarantees.

Long-term Sustainability

Open source projects offer advantages for long-term sustainability that proprietary software cannot match.

No Company Lock-in

When you rely on proprietary speech recognition, you depend on one company continuing to offer the service. If they discontinue it, pivot to a new business model, or go bankrupt, your application breaks.

Open source software doesn't depend on any single company. Even if the original developers abandon a project, the code remains available. New developers can fork it, maintain it, or improve it. This resilience protects long-term users.

The Philosophical Dimension

Beyond practical advantages, open source represents a philosophy about technology and society. It asserts that critical software should be transparent, that users deserve to understand tools they depend on, and that collaboration produces better outcomes than secrecy.

For diary applications specifically, this philosophy aligns perfectly with journaling values. A diary should be private, personal, and under your control. Open source speech recognition extends these values to the technology layer.

Conclusion: Trust, Verified

When you speak your private thoughts to a diary app, you deserve to know exactly what happens to your voice. Proprietary speech recognition asks you to trust corporate promises. Open source lets you verify those promises through auditable code.

Sherpa ONNX provides Hello Diary with speech recognition that's transparent, privacy-preserving, and community-verified. You're not trusting Hello Diary to protect your privacy—you're using technology that makes privacy violations technically impossible and verifiably so.