REPRESENTATION FANCIFUL WORD

Brand Owner (click to sort) Address Description
E ELITAIR TECNOWIND S.P.A. Piani di Marischio 113 Fabriano (Ancona) Italy Representation of the fanciful word ELITAIR in small type, the portion ELIT in thick full lines, the portion AIR in thin full lines, below each of the letters I a small corresponding circle or point, half-coloured; on the left side, device having substantially the shape of a ring in thick, half-coloured line, horizontally divided into an upper half with a horizontal diameter in thick, half-coloured line, and a lower half, the whole suggesting a fanciful small letter E.;Color is not claimed as a feature of the mark.;[ Air suction and purifying units for commercial, industrial or domestic use; ] exhaust suction and filtering hoods for kitchens; [ cooking rings both electric and gas-powered, kitchen ovens, refrigerators, electric coffee-making machines ];
E ELITAIR VAYU S.p.A. Via Piani di Marischio, 19 I-60044 Fabriano (AN) Italy Representation of the fanciful word ELITAIR in small type, the portion ELIT in thick full lines, the portion AIR in thin full lines, below each of the letters I a small corresponding circle or point, half-coloured; on the left side, device having substantially the shape of a ring in thick, half-coloured line, horizontally divided into an upper half with a horizontal diameter in thick, half-coloured line, and a lower half, the whole suggesting a fanciful small letter E.;Color is not claimed as a feature of the mark.;[ Air suction and purifying units for commercial, industrial or domestic use; ] exhaust suction and filtering hoods for kitchens; [ cooking rings both electric and gas-powered, kitchen ovens, refrigerators, electric coffee-making machines ];
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. A speech recognition system provides a subword decoder and a dictionary lookup to process a spoken input. In a first stage of processing, the subword decoder decodes the speech input based on subword units or particles and identifies hypothesized subword sequences using a particle dictionary and particle language model, but independently of a word dictionary or word vocabulary. Further stages of processing involve a particle to word graph expander and a word decoder. The particle to word graph expander expands the subword representation produced by the subword decoder into a word graph of word candidates using a word dictionary. The word decoder uses the word dictionary and a word language model to determine a best sequence of word candidates from the word graph that is most likely to match the words of the spoken input.