Speech Recognition On Switchboard Hub500

Percentage error

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Vergleichstabelle

Modellname	Percentage error
Modell 1	11
Modell 2	12.9
Modell 3	12.9
the-ibm-2015-english-conversational-telephone	8.0
the-microsoft-2016-conversational-speech	6.2
Modell 6	11.5
Modell 7	18.5
the-ibm-2016-english-conversational-telephone	6.6
building-dnn-acoustic-models-for-large	16
Modell 10	12.9
Modell 11	10.4
deep-speech-scaling-up-end-to-end-speech	12.6
single-headed-attention-based-sequence-to	4.7
building-dnn-acoustic-models-for-large	15
achieving-human-parity-in-conversational	6.6
the-microsoft-2016-conversational-speech	6.3
on-the-limit-of-english-conversational-speech	4.3
english-conversational-telephone-speech	5.5
Modell 19	12.6
the-microsoft-2016-conversational-speech	6.9
Modell 21	8.5
deep-speech-scaling-up-end-to-end-speech	12.6
Modell 23	9.2
the-ibm-2016-english-conversational-telephone	6.9
Modell 25	12.9
Modell 26	16.1
deep-speech-scaling-up-end-to-end-speech	20
achieving-human-parity-in-conversational	5.8
Modell 29	12.6
very-deep-multilingual-convolutional-neural	12.2