◾State of art speech recognition algorithms for efficient speech recognition. CMUSphinx tools are designed specifically for low-resource platforms ◾ Flexible design ◾ Focus on practical application development and not on research ◾ Support for several languages like US English, UK English, French, Mandarin, German, Dutch, Russian and ability to build a models for others ◾ BSD-like license which allows commercial distribution ◾ Commercial support ◾ Active development and release schedule ◾ Active community (more than 400 users on Linkedin CMUSphinx group) ◾ Wide range of tools for many speech-recognition related purposes (keyword spotting, alignment, pronuncation evaluation)

• An open-source software (see terms and conditions of license) • Real-time, hi-speed, accurate recognition based on 2-pass strategy. • Low memory requirement: less than 32MBytes required for work area (<64MBytes for 20k-word dictation with on-memory 3-gram LM). • Supports LM of N-gram, grammar, and isolated word. • Language and unit-dependent: Any LM in ARPA standard format and AM in HTK ascii hmmdefs format can be used. • Highly configurable: can set various search parameters. Also alternate decoding algorithm (1-best/word-pair approx., word trellis/word graph intermediates, etc.) can be chosen. • Full source code documentation and manual in Engligh / Japanese. • List of major supported features: ◦On-the-fly recognition for microphone and network input ◦GMM-based input rejection ◦Successive decoding, delimiting input by short pauses ◦N-best output ◦Word graph output ◦Forced alignment on word, phoneme, and state level ◦Confidence scoring ◦Server mode and control API ◦Many search parameters for tuning its performance ◦Character code conversion for result output. ◦(Rev. 4) Engine becomes Library and offers simple API ◦(Rev. 4) Long N-gram support ◦(Rev. 4) Run with forward / backward N-gram only ◦(Rev. 4) Confusion network output ◦(Rev. 4) Arbitrary multi-model decoding in a single thread. ◦(Rev. 4) Rapid isolated word recognition ◦(Rev. 4) User-defined LM function embedding