parakeet-unified-en-0.6b

Model overview

Parakeet-unified-en-0.6b is an English automatic speech recognition (ASR) model based on transducer architecture (RNN-T) combining both offline and streaming inference (with a minimum latency of 160ms) in one model [1]. It is trained mostly on the English part of the Granary dataset [4], which contains approximately 250,000 hours of US English (en-US) speech across diverse acoustic conditions. The model transcribes speech to English alphabet, spaces, and apostrophes with punctuation and captalization support. Average WER comparison on the HF ASR Leaderboard datasets including offline and streaming inference with different latency values. This model consists of a 🦜 Parakeet (FastConformer) encoder (jointly trained in offline and streaming modes) with an RNN-T decoder. It is designed for offline and streaming speech-to-text applications where latency can be as low as 160ms, such as voice assistants, live captioning, and conversational AI systems. The current inference pipeline supports only buffered streaming (left context is recomputed for each chunk) that can be longer than cache-aware streaming.

Key features

特点摘要待依据来源补齐，不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

Frequently asked questions

Sources & traceability

许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。