| tech,3-1-H01-1055,ak | Recent advances in <term> Automatic Speech Recognition technology </term> have put the goal of naturally sounding <term> dialog systems </term> within reach . | #914 Recent advances inAutomatic Speech Recognition technology have put the goal of naturally sounding dialog systems within reach. | |
| tech,14-1-H01-1055,ak | Recent advances in <term> Automatic Speech Recognition technology </term> have put the goal of naturally sounding <term> dialog systems </term> within reach . | #925 Recent advances in Automatic Speech Recognition technology have put the goal of naturally soundingdialog systems within reach. | |
| tech,4-2-H01-1055,ak | However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> . | #934 However, the improvedspeech recognition has brought to light a new problem: as dialog systems understand more of what the user tells them, they need to be more sophisticated at responding to the user. | |
| tech,15-2-H01-1055,ak | However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> . | #945 However, the improved speech recognition has brought to light a new problem: asdialog systems understand more of what the user tells them, they need to be more sophisticated at responding to the user. | |
| other,22-2-H01-1055,ak | However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> . | #952 However, the improved speech recognition has brought to light a new problem: as dialog systems understand more of what theuser tells them, they need to be more sophisticated at responding to the user. | |
| other,36-2-H01-1055,ak | However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> . | #966 However, the improved speech recognition has brought to light a new problem: as dialog systems understand more of what the user tells them, they need to be more sophisticated at responding to theuser. | |
| other,3-3-H01-1055,ak | The issue of <term> system response </term> to <term> users </term> has been extensively studied by the <term> natural language generation community </term> , though rarely in the context of <term> dialog systems </term> . | #971 The issue ofsystem response to users has been extensively studied by the natural language generation community, though rarely in the context of dialog systems. | |
| other,6-3-H01-1055,ak | The issue of <term> system response </term> to <term> users </term> has been extensively studied by the <term> natural language generation community </term> , though rarely in the context of <term> dialog systems </term> . | #974 The issue of system response tousers has been extensively studied by the natural language generation community, though rarely in the context of dialog systems. | |
| other,13-3-H01-1055,ak | The issue of <term> system response </term> to <term> users </term> has been extensively studied by the <term> natural language generation community </term> , though rarely in the context of <term> dialog systems </term> . | #981 The issue of system response to users has been extensively studied by thenatural language generation community, though rarely in the context of dialog systems. | |
| tech,24-3-H01-1055,ak | The issue of <term> system response </term> to <term> users </term> has been extensively studied by the <term> natural language generation community </term> , though rarely in the context of <term> dialog systems </term> . | #992 The issue of system response to users has been extensively studied by the natural language generation community, though rarely in the context ofdialog systems. | |
| tech,5-4-H01-1055,ak | We show how research in <term> generation </term> can be adapted to <term> dialog systems </term> , and how the high cost of hand-crafting <term> knowledge-based generation systems </term> can be overcome by employing <term> machine learning techniques </term> . | #1000 We show how research ingeneration can be adapted to dialog systems, and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employing machine learning techniques. | |
| tech,10-4-H01-1055,ak | We show how research in <term> generation </term> can be adapted to <term> dialog systems </term> , and how the high cost of hand-crafting <term> knowledge-based generation systems </term> can be overcome by employing <term> machine learning techniques </term> . | #1005 We show how research in generation can be adapted todialog systems, and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employing machine learning techniques. | |
| tech,20-4-H01-1055,ak | We show how research in <term> generation </term> can be adapted to <term> dialog systems </term> , and how the high cost of hand-crafting <term> knowledge-based generation systems </term> can be overcome by employing <term> machine learning techniques </term> . | #1015 We show how research in generation can be adapted to dialog systems, and how the high cost of hand-craftingknowledge-based generation systems can be overcome by employing machine learning techniques. | |
| tech,28-4-H01-1055,ak | We show how research in <term> generation </term> can be adapted to <term> dialog systems </term> , and how the high cost of hand-crafting <term> knowledge-based generation systems </term> can be overcome by employing <term> machine learning techniques </term> . | #1023 We show how research in generation can be adapted to dialog systems, and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employingmachine learning techniques. |
